Prosecution Insights
Last updated: April 19, 2026
Application No. 18/046,227

DECODER FOR DECODING WEIGHT PARAMETERS OF A NEURAL NETWORK, ENCODER, METHODS AND ENCODED REPRESENTATION USING PROBABILITY ESTIMATION PARAMETERS

Non-Final OA §101
Filed
Oct 13, 2022
Examiner
SAEED, USMAAN
Art Unit
2146
Tech Center
2100 — Computer Architecture & Software
Assignee
Fraunhofer-Gesellschaft zur Förderung der angewandten Forschung e.V.
OA Round
2 (Non-Final)
51%
Grant Probability
Moderate
2-3
OA Rounds
5y 5m
To Grant
96%
With Interview

Examiner Intelligence

Grants 51% of resolved cases
51%
Career Allow Rate
74 granted / 146 resolved
-4.3% vs TC avg
Strong +46% interview lift
Without
With
+45.8%
Interview Lift
resolved cases with interview
Typical timeline
5y 5m
Avg Prosecution
12 currently pending
Career history
158
Total Applications
across all art units

Statute-Specific Performance

§101
19.3%
-20.7% vs TC avg
§103
55.7%
+15.7% vs TC avg
§102
10.1%
-29.9% vs TC avg
§112
9.1%
-30.9% vs TC avg
Black line = Tech Center average estimate • Based on career data from 146 resolved cases

Office Action

§101
DETAILED ACTION Notice of Pre-AIA or AIA Status The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . This office action is responsive to the amendments filed November 29, 2025. Claims 62, 63, 82, 83, 84, 85, 86, and 87, are amended. Claims 1-61, 64, 70-73, 75, and 77-81are canceled. Claims 62-63, 65-69, 74, 76, and 82-87 are pending in this office action. Information Disclosure Statement The information disclosure statements (IDS) submitted on 01/15/2026 and 01/27/2026 are in compliance with the provisions of 37 CFR 1.97 and have been considered by the examiner. Claim Objections Claims 62, 63, 82-86 are objected to because of the following informalities: These claims recite “… is implemented using a hardware apparatus, or using a computer, or using a combination of a hardware apparatus and a computer.” This should be corrected to recite “… is implemented using a hardware apparatus, or using a computer, or using a combination of the hardware apparatus and the computer.” Appropriate correction is required. Claim Rejections - 35 USC § 101 35 U.S.C. 101 reads as follows: Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title. Claims 62-63, 65-69, 74, 76, and 82-87 are rejected under 35 U.S.C. 101 because the claims are directed to an abstract idea without significantly more. Regarding claim 62, in Step 1 of the 101 analysis set forth in MPEP 2106, the claim recites "A decoder for decoding weight parameters of a neural network...". This claim is directed to a machine which is one of the four statutory categories of invention. In Step 2a Pong 1 of the 101 analysis set forth in the MPEP 2106, the examiner has determined that the following limitations recite a process that, under the broadest reasonable interpretation, covers abstract ideas but for recitation of generic computer components: “A decoder for decoding weight parameters of a neural network, wherein the decoder is configured to decode the neural network parameters of the neural network using a context-dependent arithmetic decoding” is a mathematical concept in view of specification pages 34-35 (See MPEP 2106.04(a)(2)(I)). “wherein the decoder is configured to acquire a probability estimate for a decoding of a bin of a number representation of a neural network parameter using one or more probability estimation parameters” is a mathematical concept in view of specification pages 34-35 (See MPEP 2106.04(a)(2)(I)). “wherein the decoder is configured to use different probability estimation parameter values for a decoding of different neural network parameters and/or to use different probability estimation parameter values for a decoding of bins associated with different context models” is a mathematical concept in view of specification pages 34-35 (See MPEP 2106.04(a)(2)(I)). “wherein the decoder is configured to determine one or more state variables and to derive the probability estimate using the one or more state variables” is a mathematical concept in view of specification pages 34-35 (See MPEP 2106.04(a)(2)(I)). “wherein the decoder is configured to update the state variables PNG media_image1.png 22 48 media_image1.png Greyscale according to PNG media_image2.png 148 468 media_image2.png Greyscale ” is a mathematical concept in view the recited formula and in view of specification pages 34-35 (See MPEP 2106.04(a)(2)(I)). “wherein the decoder is configured to vary the weighting factors PNG media_image3.png 26 24 media_image3.png Greyscale , so as to use different probability estimation parameter values for a decoding of different neural network parameters and/or to use different probability estimation parameter values for a decoding of bins associated with different context models and/or to use different probability estimation parameter values for a decoding of neural network parameters associated with different layers of the neural network” is a mathematical concept in view of specification pages 33-36 (See MPEP 2106.04(a)(2)(I)). If claim limitations, under their broadest reasonable interpretation, covers performance of the limitations as mathematical concepts but for the recitation of generic computer components, then it falls within the mathematical concept grouping of abstract ideas. According, the claim "recites" an abstract idea. In Step 2a Prong 2 of the 101-analysis set forth in MPEP 2106, the examiner has determined that the following additional elements do not integrate this judicial exception into a practical application: “wherein the decoder is configured to acquire a plurality of neural network parameters of the neural network on the basis of an encoded bitstream” is an insignificant extra solution activity of mere data gathering (See MPEP 2106.05(g)). “wherein the decoder is implemented using a hardware apparatus, or using a computer, or using a combination of a hardware apparatus and a computer” is mere instructions to apply the judicial exception using generic computer components (See MPEP 2106.05(f)). Since the claim as a whole, looking at the additional elements individually and in combination, does not contain any other additional elements that are indicative of integration into a practical application, the claim is directed to an abstract idea. In Step 2b of the 101-analysis set forth in the 2019 PEG, the examiner has determined that the claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. “wherein the decoder is configured to acquire a plurality of neural network parameters of the neural network on the basis of an encoded bitstream” is an insignificant extra solution activity of mere data gathering (See MPEP 2106.05(g)). Under step 2B, this insignificant extra solution activity is a well understood routine and conventional activity, see Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (See MPEP 2016.05(d)(ii)(i)). “wherein the decoder is implemented using a hardware apparatus, or using a computer, or using a combination of a hardware apparatus and a computer” is mere instructions to apply the judicial exception using generic computer components (See MPEP 2106.05(f)). Considering the additional elements individually and in combination, and the claim as a whole, the additional elements do not provide significantly more than the abstract idea. Therefore, the claim is not patent eligible. Regarding claim 63, in Step 1 of the 101 analysis set forth in MPEP 2106, the claim recites "A decoder for decoding weight parameters of a neural network...". This claim is directed to a machine which is one of the four statutory categories of invention. In Step 2a Pong 1 of the 101 analysis set forth in the MPEP 2106, the examiner has determined that the following limitations recite a process that, under the broadest reasonable interpretation, covers abstract ideas but for recitation of generic computer components: “A decoder for decoding weight parameters of a neural network, wherein the decoder is configured to decode the neural network parameters of the neural network using a context-dependent arithmetic decoding” is a mathematical concept in view of specification pages 34-35 (See MPEP 2106.04(a)(2)(I)). “wherein the decoder is configured to acquire a probability estimate for a decoding of a bin of a number representation of a neural network parameter using one or more probability estimation parameters” is a mathematical concept in view of specification pages 34-35 (See MPEP 2106.04(a)(2)(I)). “wherein the decoder is configured to use different probability estimation parameter values for a decoding of neural network parameters associated with different layers of the neural network” is a mathematical concept in view of specification pages 34-35 (See MPEP 2106.04(a)(2)(I)). “wherein the decoder is configured to determine one or more state variables and to derive the probability estimate using the one or more state variables” is a mathematical concept in view of specification pages 34-35 (See MPEP 2106.04(a)(2)(I)). “wherein the decoder is configured to update the state variables PNG media_image1.png 22 48 media_image1.png Greyscale according to PNG media_image2.png 148 468 media_image2.png Greyscale ” is a mathematical concept in view the recited formula and in view of specification pages 34-35 (See MPEP 2106.04(a)(2)(I)). “wherein the decoder is configured to vary the weighting factors PNG media_image3.png 26 24 media_image3.png Greyscale , so as to use different probability estimation parameter values for a decoding of different neural network parameters and/or to use different probability estimation parameter values for a decoding of bins associated with different context models and/or to use different probability estimation parameter values for a decoding of neural network parameters associated with different layers of the neural network” is a mathematical concept in view of specification pages 33-36 (See MPEP 2106.04(a)(2)(I)). If claim limitations, under their broadest reasonable interpretation, covers performance of the limitations as mathematical concepts but for the recitation of generic computer components, then it falls within the mathematical concept grouping of abstract ideas. According, the claim "recites" an abstract idea. In Step 2a Prong 2 of the 101-analysis set forth in MPEP 2106, the examiner has determined that the following additional elements do not integrate this judicial exception into a practical application: “wherein the decoder is configured to acquire a plurality of neural network parameters of the neural network on the basis of an encoded bitstream” is an insignificant extra solution activity of mere data gathering (See MPEP 2106.05(g)). “wherein the decoder is implemented using a hardware apparatus, or using a computer, or using a combination of a hardware apparatus and a computer” is mere instructions to apply the judicial exception using generic computer components (See MPEP 2106.05(f)). Since the claim as a whole, looking at the additional elements individually and in combination, does not contain any other additional elements that are indicative of integration into a practical application, the claim is directed to an abstract idea. In Step 2b of the 101-analysis set forth in the 2019 PEG, the examiner has determined that the claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. “wherein the decoder is configured to acquire a plurality of neural network parameters of the neural network on the basis of an encoded bitstream” is an insignificant extra solution activity of mere data gathering (See MPEP 2106.05(g)). Under step 2B, this insignificant extra solution activity is a well understood routine and conventional activity, see Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (See MPEP 2016.05(d)(ii)(i)). “wherein the decoder is implemented using a hardware apparatus, or using a computer, or using a combination of a hardware apparatus and a computer” is mere instructions to apply the judicial exception using generic computer components (See MPEP 2106.05(f)). Considering the additional elements individually and in combination, and the claim as a whole, the additional elements do not provide significantly more than the abstract idea. Therefore, the claim is not patent eligible. Regarding claim 65 “choose one or more probability estimation parameters from different sets of useable parameter values or of useable tuples of parameter values” and “use different mapping rules mapping an encoded value representing one or more probability estimation parameters onto one or more probability estimation” A person can mentally choose probability estimation parameters and also use different mapping rules representing estimation parameter (See MPEP 2106.04(a)(2)(III)). “wherein the decoder is configured to choose … parameter values in dependence on a quantization mode and/or in dependence on a number of parameters of a layer of the neural network, or in dependence on a number of neural network parameters to be decoded using the chosen one or more probability estimation parameters, or in dependence on a number of elements of a layer parameter” Under step 2A prong II and Step 2B, these limitations are mere instructions to apply the judicial exception using generic computer components (See MPEP 2106.05(f)). “wherein the decoder is configured to use … onto one or more probability estimation parameters in dependence on a quantization mode and/or in dependence on a number of parameters of a layer of the neural network, or in dependence on a number of neural network parameters to be decoded using the chosen one or more probability estimation parameters, or in dependence on a number of elements of a layer parameter” Under step 2A prong II and Step 2B, these limitations are mere instructions to apply the judicial exception using generic computer components (See MPEP 2106.05(f)). Since the claim does not recite additional elements that either integrate the judicial exception into a practical application, nor provide significantly more than the judicial exception, the claim is not patent eligible. Regarding claim 66, “choose one or more probability estimation parameters from a first set of useable parameter values or from a first set of useable tuples of parameter values” A person can mentally choose probability estimation parameters (See MPEP 2106.04(a)(2)(III)). “wherein the decoder is configured to selectively choose… in case that a uniform quantization of the one or more probability estimation parameters is used, and/or if the number of parameters of a layer of the neural network is below a threshold value or if the number of neural network parameters to be decoded using the chosen one or more probability estimation parameters is below a threshold value, or if the number of elements of the layer parameter is below a threshold value” Under step 2A prong II and Step 2B, these limitations are mere instructions to apply the judicial exception using generic computer components (See MPEP 2106.05(f)). “choose one or more probability estimation parameters from a second set of useable parameter values or from a second set of useable tuples of parameter values” A person can mentally choose probability estimation parameters (See MPEP 2106.04(a)(2)(III)). “wherein the decoder is configured to selectively choose… in case that a variable quantization of the one or more probability estimation parameters is used, and/or if the number of parameters of a layer of the neural network is above the threshold value or if the number of neural network parameters to be decoded using the chosen one or more probability estimation parameters is above the threshold value, or if the number of elements of the layer parameter is above the threshold value” Under step 2A prong II and Step 2B, these limitations are mere instructions to apply the judicial exception using generic computer components (See MPEP 2106.05(f)). “selectively use, a first mapping rule mapping an encoded value representing one or more probability estimation parameters onto one or more probability estimation parameters” A person can mentally use a mapping rule to map a value with probability estimation parameters (See MPEP 2106.04(a)(2)(III)). “wherein the decoder is configured to use … in case that a uniform quantization of the one or more probability estimation parameters is used, and/or if the number of parameters of a layer of the neural network is below a threshold value or if the number of neural network parameters to be decoded using the chosen one or more probability estimation parameters is below a threshold value, or if the number of elements of the layer parameter is below a threshold value” Under step 2A prong II and Step 2B, these limitations are mere instructions to apply the judicial exception using generic computer components (See MPEP 2106.05(f)). “selectively use a second mapping rule mapping an encoded value representing one or more probability estimation parameters onto one or more probability estimation parameters” A person can mentally use a mapping rule to map a value with probability estimation parameters (See MPEP 2106.04(a)(2)(III)). “wherein the decoder is configured to use, … in case that a variable quantization of the one or more probability estimation parameters is used, and/or if the number of parameters of a layer of the neural network is above the threshold value or if the number of neural network parameters to be decoded using the chosen one or more probability estimation parameters is above the threshold value, or if the number of elements of the layer parameter is above the threshold value” Under step 2A prong II and Step 2B, these limitations are mere instructions to apply the judicial exception using generic computer components (See MPEP 2106.05(f)). “wherein the first set of useable parameter values is different from the second set of useable parameter values, and wherein the first set of useable tuples of parameter values is different from the second set of useable tuples of parameter values; and/or wherein the second set of useable parameter values comprises more useable parameter values than the first set of useable parameter values, and wherein the second set of useable tuples of parameter values comprises more useable tuples than the first set of useable tuples of parameter values; and/or wherein the second mapping rule is different from the first mapping rule” Under step 2A prong II and Step 2B, these limitations are mere instructions to apply the judicial exception using generic computer components (See MPEP 2106.05(f)). Since the claim does not recite additional elements that either integrate the judicial exception into a practical application, nor provide significantly more than the judicial exception, the claim is not patent eligible. Regarding claim 67, “wherein, on average, useable parameter values of the second set of useable parameter values allow for a faster adaptation of a probability estimate than useable parameter values of the first set of useable parameter values, or wherein, on average, useable tuples of parameter values of the second set of useable tuples of parameter values allow for a faster adaptation of a probability estimate than useable tuples of parameter values of the first set of useable tuples of parameter values” Under step 2A prong II and Step 2B, these limitations are mere instructions to apply the judicial exception using generic computer components (See MPEP 2106.05(f)). Since the claim does not recite additional elements that either integrate the judicial exception into a practical application, nor provide significantly more than the judicial exception, the claim is not patent eligible. Regarding claim 68, “wherein the second set of useable parameter values comprises a useable parameter value which allows for a faster adaptation of a probability estimate than useable parameter values of the first set of useable parameter values, or wherein the second set of useable tuples of parameter values comprises a useable tuple of parameter values which allows for a faster adaptation of a probability estimate than useable tuples of parameter values of the first set of useable tuples of parameter values” Under step 2A prong II and Step 2B, these limitations are mere instructions to apply the judicial exception using generic computer components (See MPEP 2106.05(f)). Since the claim does not recite additional elements that either integrate the judicial exception into a practical application, nor provide significantly more than the judicial exception, the claim is not patent eligible. Regarding claim 69 “selectively choose the one or more probability estimation parameters” A person can mentally choose probability estimation parameters (See MPEP 2106.04(a)(2)(III)). “wherein the decoder is configured to selectively choose… from an increased choice if a number of neural network parameters to be decoded using the chosen one or more probability estimation parameters is larger than or equal to a threshold value” Under step 2A prong II and Step 2B, these limitations are mere instructions to apply the judicial exception using generic computer components (See MPEP 2106.05(f)). Since the claim does not recite additional elements that either integrate the judicial exception into a practical application, nor provide significantly more than the judicial exception, the claim is not patent eligible. Regarding claim 74, “wherein the decoder is configured to vary a number of bins or a maximum number of bins used for decoding the one or more probability estimation parameters in dependence on a quantization mode used for quantizing the one or more probability estimation parameters; and/or in dependence on a number of parameters of a layer of the neural network, or in dependence on a number of neural network parameters to be decoded using the one or more probability estimation parameters, or in dependence on a number of elements of a layer parameter” is a mathematical concept in view of specification pages 34-35 (See MPEP 2106.04(a)(2)(I)). Since the claim does not recite additional elements that either integrate the judicial exception into a practical application, nor provide significantly more than the judicial exception, the claim is not patent eligible. Regarding claim 76 “wherein the decoder is configured to vary a number of bins or a maximum number of bins used for decoding the one or more probability estimation parameters designating a selected probability estimation parameter or a selected tuple of probability estimation parameters in accordance with a switching between different sets of usable parameter values associated with the one or more probability estimation parameters, or between different sets of tuples of useable parameter values associated with a plurality of probability estimation parameters or between different mapping rules” is a mathematical concept in view of specification pages 34-35 (See MPEP 2106.04(a)(2)(I)). Since the claim does not recite additional elements that either integrate the judicial exception into a practical application, nor provide significantly more than the judicial exception, the claim is not patent eligible. Regarding claim 82, in Step 1 of the 101 analysis set forth in MPEP 2106, the claim recites "An encoder for encoding weight parameters of a neural network...". This claim is directed to a machine which is one of the four statutory categories of invention. In Step 2a Pong 1 of the 101 analysis set forth in the MPEP 2106, the examiner has determined that the following limitations recite a process that, under the broadest reasonable interpretation, covers abstract ideas but for recitation of generic computer components: “An encoder for encoding weight parameters of a neural network, wherein the encoder is configured to encode the neural network parameters of the neural network using a context-dependent arithmetic coding” is a mathematical concept in view of specification pages 45-46 (See MPEP 2106.04(a)(2)(I)). “wherein the encoder is configured to acquire a probability estimate for an encoding of a bin of a number representation of a neural network parameter using one or more probability estimation parameters” is a mathematical concept in view of specification pages 45-46 (See MPEP 2106.04(a)(2)(I)). “wherein the encoder is configured to use different probability estimation parameter values for an encoding of different neural network parameters and/or to use different probability estimation parameter values for an encoding of bins associated with different context models” is a mathematical concept in view of specification pages 45-46 (See MPEP 2106.04(a)(2)(I)). “wherein the encoder is configured to use different probability estimation parameter values for an encoding of neural network parameters associated with different layers of the neural network” is a mathematical concept in view of specification pages 45-46 (See MPEP 2106.04(a)(2)(I)). “wherein the encoder is configured to determine one or more state variables and to derive the probability estimate using the one or more state variables” is a mathematical concept in view of specification pages 45-46 (See MPEP 2106.04(a)(2)(I)). “wherein the encoder is configured to update the state variables PNG media_image1.png 22 48 media_image1.png Greyscale according to PNG media_image2.png 148 468 media_image2.png Greyscale ” is a mathematical concept in view the recited formula and in view of specification pages 45-46 (See MPEP 2106.04(a)(2)(I)). “wherein the encoder is configured to vary the weighting factors PNG media_image3.png 26 24 media_image3.png Greyscale , so as to use different probability estimation parameter values for an encoding of different neural network parameters and/or to use different probability estimation parameter values for an encoding of bins associated with different context models and/or to use different probability estimation parameter values for an encoding of neural network parameters associated with different layers of the neural network” is a mathematical concept in view of specification pages 44-47 (See MPEP 2106.04(a)(2)(I)). If claim limitations, under their broadest reasonable interpretation, covers performance of the limitations as mathematical concepts but for the recitation of generic computer components, then it falls within the mathematical concept grouping of abstract ideas. According, the claim "recites" an abstract idea. In Step 2a Prong 2 of the 101-analysis set forth in MPEP 2106, the examiner has determined that the following additional elements do not integrate this judicial exception into a practical application: “wherein the encoder is configured to acquire a plurality of neural network parameters of the neural network” is an insignificant extra solution activity of mere data gathering (See MPEP 2106.05(g)). “wherein the encoder is implemented using a hardware apparatus, or using a computer, or using a combination of a hardware apparatus and a computer” is mere instructions to apply the judicial exception using generic computer components (See MPEP 2106.05(f)). Since the claim as a whole, looking at the additional elements individually and in combination, does not contain any other additional elements that are indicative of integration into a practical application, the claim is directed to an abstract idea. In Step 2b of the 101-analysis set forth in the 2019 PEG, the examiner has determined that the claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. “wherein the encoder is configured to acquire a plurality of neural network parameters of the neural network” is an insignificant extra solution activity of mere data gathering (See MPEP 2106.05(g)). Under step 2B, this insignificant extra solution activity is a well understood routine and conventional activity, see Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (See MPEP 2016.05(d)(ii)(i)). “wherein the encoder is implemented using a hardware apparatus, or using a computer, or using a combination of a hardware apparatus and a computer” is mere instructions to apply the judicial exception using generic computer components (See MPEP 2106.05(f)). Considering the additional elements individually and in combination, and the claim as a whole, the additional elements do not provide significantly more than the abstract idea. Therefore, the claim is not patent eligible. Claims 83 and 84 recite similar limitations as recited in claims 62, 63 and 82 except that they set forth the claimed invention as a method and are rejected for similar reasons as applied hereinabove. Claims 85 and 86 recite similar limitations as recited in claims 62, 63 and 82 except that they set forth the claimed invention as a non-transitory digital storage medium having stored thereon a computer program and are rejected for similar reasons as applied hereinabove. Claims 85 and 86 recite additional limitation of “A non-transitory digital storage medium having stored thereon a computer program for performing a method for decoding weight parameters of a neural network” which under step 2A prong II and Step 2B is mere instructions to apply the judicial exception using generic computer components (See MPEP 2106.05(f)). Since the claim does not recite additional elements that either integrate the judicial exception into a practical application, nor provide significantly more than the judicial exception, the claim is not patent eligible. Regarding claim 87, in Step 1 of the 101 analysis set forth in MPEP 2106, the claim recites "A non-transitory digital storage medium...". This claim is directed to a machine/product which is one of the four statutory categories of invention. In Step 2a Pong 1 of the 101 analysis set forth in the MPEP 2106, the examiner has determined that the following limitations recite a process that, under the broadest reasonable interpretation, covers abstract ideas but for recitation of generic computer components: “determining characteristics of a probability estimation for an adaptation of a context of an arithmetic decoding of the encoded weight parameters” A person can mentally determine characteristics of an estimation (See MPEP 2106.04(a)(2)(III)). “wherein the one or more probability estimation parameters comprise weighting factors PNG media_image4.png 20 24 media_image4.png Greyscale for updating state variables PNG media_image1.png 22 48 media_image1.png Greyscale according to PNG media_image5.png 80 460 media_image5.png Greyscale ” is a mathematical concept in view the recited formula and in view of specification pages 34-35 and 45-46 (See MPEP 2106.04(a)(2)(I)). “in order to acquire a probability estimate, based on the state variables, for a decoding of a bin of a number representation of a neural network parameter, wherein mₖ are weighting factors, wherein A is a lookup table and wherein Z is an offset value” is a mathematical concept in view of specification pages 34-35 and 45-46 (See MPEP 2106.04(a)(2)(I)). “wherein the signaling indicates a variation of the weighting factors PNG media_image3.png 26 24 media_image3.png Greyscale , so as to use different probability estimation parameter values for a decoding of different neural network parameters and/or to use different probability estimation parameter values for a decoding of bins associated with different context models and/or to use different probability estimation parameter values for a decoding of neural network parameters associated with different layers of the neural network” is a mathematical concept in view of specification pages 34-35 and 45-46 (See MPEP 2106.04(a)(2)(I)). If claim limitations, under their broadest reasonable interpretation, covers performance of the limitations as mathematical concepts or mental processes but for the recitation of generic computer components, then it falls within the mathematical concept/mental process grouping of abstract ideas. According, the claim "recites" an abstract idea. In Step 2a Prong 2 of the 101-analysis set forth in MPEP 2106, the examiner has determined that the following additional elements do not integrate this judicial exception into a practical application: “A non-transitory digital storage medium having stored thereon an encoded representation of weight parameters of a neural network, the encoded representation comprising: a plurality of encoded weight parameters of the neural network” is mere instructions to apply the judicial exception using generic computer components (See MPEP 2106.05(f)). “an encoded representation of a signaling, the signaling indicating a selection of one or more probability estimation parameters, the probability estimation parameters” is mere instructions to apply the judicial exception using generic computer components (See MPEP 2106.05(f)). Since the claim as a whole, looking at the additional elements individually and in combination, does not contain any other additional elements that are indicative of integration into a practical application, the claim is directed to an abstract idea. In Step 2b of the 101-analysis set forth in the 2019 PEG, the examiner has determined that the claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. “A non-transitory digital storage medium having stored thereon an encoded representation of weight parameters of a neural network, the encoded representation comprising: a plurality of encoded weight parameters of the neural network” is mere instructions to apply the judicial exception using generic computer components (See MPEP 2106.05(f)). “an encoded representation of a signaling, the signaling indicating a selection of one or more probability estimation parameters, the probability estimation parameters” is mere instructions to apply the judicial exception using generic computer components (See MPEP 2106.05(f)). Considering the additional elements individually and in combination, and the claim as a whole, the additional elements do not provide significantly more than the abstract idea. Therefore, the claim is not patent eligible. Response to Arguments Applicant's arguments with respect to 35 USC 103 have been fully considered and are persuasive. The 35 USC 103 rejection has been withdrawn. Applicant's arguments with respect to 35 USC 101 have been fully considered but they are not persuasive. In the new rejection above examiner has clarified the rejections to show “A decoder for decoding weight parameters of a neural network, wherein the decoder is configured to decode the neural network parameters of the neural network using a context-dependent arithmetic decoding” is a mathematical concept in view of specification pages 34-35 (See MPEP 2106.04(a)(2)(I)), “wherein the decoder is configured to acquire a probability estimate for a decoding of a bin of a number representation of a neural network parameter using one or more probability estimation parameters” is a mathematical concept in view of specification pages 34-35 (See MPEP 2106.04(a)(2)(I)), “wherein the decoder is configured to use different probability estimation parameter values for a decoding of different neural network parameters and/or to use different probability estimation parameter values for a decoding of bins associated with different context models” is a mathematical concept in view of specification pages 34-35 (See MPEP 2106.04(a)(2)(I)), “wherein the decoder is configured to determine one or more state variables and to derive the probability estimate using the one or more state variables” is a mathematical concept in view of specification pages 34-35 (See MPEP 2106.04(a)(2)(I)), “wherein the decoder is configured to update the state variables PNG media_image1.png 22 48 media_image1.png Greyscale according to PNG media_image2.png 148 468 media_image2.png Greyscale ” is a mathematical concept in view the recited formula and in view of specification pages 34-35 (See MPEP 2106.04(a)(2)(I)) and “wherein the decoder is configured to vary the weighting factors PNG media_image3.png 26 24 media_image3.png Greyscale , so as to use different probability estimation parameter values for a decoding of different neural network parameters and/or to use different probability estimation parameter values for a decoding of bins associated with different context models and/or to use different probability estimation parameter values for a decoding of neural network parameters associated with different layers of the neural network” is a mathematical concept in view of specification pages 33-36 (See MPEP 2106.04(a)(2)(I)). In Step 2a Prong 2 of the 101-analysis set forth in MPEP 2106, the examiner has determined that the following additional elements do not integrate this judicial exception into a practical application: “wherein the decoder is configured to acquire a plurality of neural network parameters of the neural network on the basis of an encoded bitstream” is an insignificant extra solution activity of mere data gathering (See MPEP 2106.05(g)) and “wherein the decoder is implemented using a hardware apparatus, or using a computer, or using a combination of a hardware apparatus and a computer” is mere instructions to apply the judicial exception using generic computer components (See MPEP 2106.05(f)). Since the claim as a whole, looking at the additional elements individually and in combination, does not contain any other additional elements that are indicative of integration into a practical application, the claim is directed to an abstract idea. In Step 2b of the 101-analysis set forth in the 2019 PEG, the examiner has determined that the claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. “Wherein the decoder is configured to acquire a plurality of neural network parameters of the neural network on the basis of an encoded bitstream” is an insignificant extra solution activity of mere data gathering (See MPEP 2106.05(g)). Under step 2B, this insignificant extra solution activity is a well understood routine and conventional activity, see Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (See MPEP 2016.05(d)(ii)(i)) and “wherein the decoder is implemented using a hardware apparatus, or using a computer, or using a combination of a hardware apparatus and a computer” is mere instructions to apply the judicial exception using generic computer components (See MPEP 2106.05(f)). Considering the additional elements individually and in combination, and the claim as a whole, the additional elements do not provide significantly more than the abstract idea. Therefore, the claims are not patent eligible. Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to Usmaan Saeed whose telephone number is (571)272-4046. The examiner can normally be reached Monday-Friday 9:00am - 5:30pm. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s Director, David Wiley can be reached at 571-272-4150. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /USMAAN SAEED/ Supervisory Patent Examiner, Art Unit 2146
Read full office action

Prosecution Timeline

Oct 13, 2022
Application Filed
Jul 26, 2025
Non-Final Rejection — §101
Nov 29, 2025
Response Filed
Mar 15, 2026
Non-Final Rejection — §101 (current)

Precedent Cases

Applications granted by this same examiner with similar technology

Patent 12566955
METHOD FOR TRAINING A NEURAL NETWORK
2y 5m to grant Granted Mar 03, 2026
Patent 12566971
METHODS FOR TRAINING AN INDUSTRIAL QUESTION-ANSWERING MODEL BASED ON REINFORCEMENT LEARNING AND KNOWLEDGE BASE MATCHING
2y 5m to grant Granted Mar 03, 2026
Patent 12549003
Intrinsic Biasing Method for a Dual DC/DC Converter
2y 5m to grant Granted Feb 10, 2026
Patent 11544288
SYSTEMS AND METHODS FOR MANAGING DISTRIBUTED DATABASE DEPLOYMENTS
2y 5m to grant Granted Jan 03, 2023
Patent 9684639
EFFICIENT VALIDATION OF BINARY XML DATA
2y 5m to grant Granted Jun 20, 2017
Study what changed to get past this examiner. Based on 5 most recent grants.

AI Strategy Recommendation

Get an AI-powered prosecution strategy using examiner precedents, rejection analysis, and claim mapping.
Powered by AI — typically takes 5-10 seconds

Prosecution Projections

2-3
Expected OA Rounds
51%
Grant Probability
96%
With Interview (+45.8%)
5y 5m
Median Time to Grant
Moderate
PTA Risk
Based on 146 resolved cases by this examiner. Grant probability derived from career allow rate.

Sign in with your work email

Enter your email to receive a magic link. No password needed.

Personal email addresses (Gmail, Yahoo, etc.) are not accepted.

Free tier: 3 strategy analyses per month