Paper Citation Record · LEDGER

DeepHoyer: Learning Sparser Neural Network with Differentiable Scale-Invariant Sparsity Measures

As of 18 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 2 inbound Pith citation observations for arXiv:1908.09979.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
1908.09979 v2

Coverage vector

measured 24 of 24 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T11:02:01.461598Z

measured 26 of 26 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T19:14:53.759102Z

measured 1 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

24 of 24 outbound references displayed

verified exact2
verified fuzzy12
unresolved10
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

13
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation 5a153319-664e-472c-918e-e2b96969192c · outbound

This paper cites For all the tables, the results of previous works are listed on the top, and are ordered based on publication year.

DeepHoyer: Learning Sparser Neural Network with Differentiable Scale-Invariant Sparsity Measures For all the tables, the results of previous works are listed on the top, and are ordered based on publication year

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:02:01.703262Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 8d70a857-c3ae-4a87-82b3-077c1d454463 · outbound

This paper cites Soft Filter Pruning for Accelerating Deep Convolutional Neural Networks.

DeepHoyer: Learning Sparser Neural Network with Differentiable Scale-Invariant Sparsity Measures Soft Filter Pruning for Accelerating Deep Convolutional Neural Networks

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-14T11:02:01.360339Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 85d14f58-4904-4338-8d49-d8894abef068 · outbound

This paper cites ILSVRC2012.

DeepHoyer: Learning Sparser Neural Network with Differentiable Scale-Invariant Sparsity Measures ILSVRC2012

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:02:01.747480Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation d3005d4e-1a07-4149-a075-dbcc88090af0 · outbound

This paper cites Pruning Filters for Efficient ConvNets.

DeepHoyer: Learning Sparser Neural Network with Differentiable Scale-Invariant Sparsity Measures Pruning Filters for Efficient ConvNets

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-14T11:02:01.376149Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 80ec97a7-0451-4557-9b28-99d4cdbc7943 · outbound

This paper cites Learning Sparse Neural Networks through $L_0$ Regularization.

DeepHoyer: Learning Sparser Neural Network with Differentiable Scale-Invariant Sparsity Measures Learning Sparse Neural Networks through $L_0$ Regularization

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-14T11:02:01.381058Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation af47dfd7-fd36-4cb3-a65d-ce7cbed2b0ab · outbound

This paper cites Deep supervised learning for hyperspectral data classiﬁcation through convolutional neural net- works.

DeepHoyer: Learning Sparser Neural Network with Differentiable Scale-Invariant Sparsity Measures Deep supervised learning for hyperspectral data classiﬁcation through convolutional neural net- works

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:02:01.821270Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation a730f5b3-27d6-4b14-8973-0886fbabf6ee · outbound

This paper cites Faster CNNs with Direct Sparse Convolutions and Guided Pruning.

DeepHoyer: Learning Sparser Neural Network with Differentiable Scale-Invariant Sparsity Measures Faster CNNs with Direct Sparse Convolutions and Guided Pruning

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-14T11:02:01.397216Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6249a67c-c071-4153-9db5-d4cd8263886c · outbound

This paper cites Very Deep Convolutional Networks for Large-Scale Image Recognition.

DeepHoyer: Learning Sparser Neural Network with Differentiable Scale-Invariant Sparsity Measures Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-14T11:02:01.402452Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1ee39cfa-974f-4c5f-adac-ad834eb5f480 · outbound

This paper cites Leveraging Filter Correlations for Deep Model Compression.

DeepHoyer: Learning Sparser Neural Network with Differentiable Scale-Invariant Sparsity Measures Leveraging Filter Correlations for Deep Model Compression

Reference 14

Resolution: verified exact; local_arxiv, observed 2026-08-14T11:02:01.544496Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 8a13540b-f604-42bd-9e4e-bc5c03fc96c8 · outbound

This paper cites Reconstruction of jointly sparse vectors via manifold optimization.

DeepHoyer: Learning Sparser Neural Network with Differentiable Scale-Invariant Sparsity Measures Reconstruction of jointly sparse vectors via manifold optimization

Reference 15

Resolution: verified exact; local_arxiv, observed 2026-08-14T11:02:01.522916Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation a586cd79-5395-4aa9-81ea-444b4050e186 · outbound

This paper cites Learning Intrinsic Sparse Structures within Long Short-Term Memory.

DeepHoyer: Learning Sparser Neural Network with Differentiable Scale-Invariant Sparsity Measures Learning Intrinsic Sparse Structures within Long Short-Term Memory

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-14T11:02:01.421954Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6b41a21d-a213-4b80-a2d0-731530f97d22 · outbound

This paper cites Model selection and estimation in regression with grouped variables.

DeepHoyer: Learning Sparser Neural Network with Differentiable Scale-Invariant Sparsity Measures Model selection and estimation in regression with grouped variables

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:02:01.791931Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 087f38be-f08b-4868-a7b2-b1f4941772fb · outbound

This paper cites an elementwj in the weight matrixW.

DeepHoyer: Learning Sparser Neural Network with Differentiable Scale-Invariant Sparsity Measures an elementwj in the weight matrixW

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:02:01.777965Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 2ad0aec7-23fe-4a97-b1e1-ce0641a37679 · outbound

This paper cites All the MNIST experiments are done with a single TITAN XP GPU.

DeepHoyer: Learning Sparser Neural Network with Differentiable Scale-Invariant Sparsity Measures All the MNIST experiments are done with a single TITAN XP GPU

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:02:01.762891Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation ca28459a-cf74-44ac-ae49-4053cc46f667 · outbound

This paper cites torchvision.

DeepHoyer: Learning Sparser Neural Network with Differentiable Scale-Invariant Sparsity Measures torchvision

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:02:01.733220Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 151bd09f-2fb5-4e5d-aab4-0c100bb5210e · outbound

This paper cites Since most of the weight elements will be zero in the end, we only plot the histogram of nonzero weight elements for better observation.

DeepHoyer: Learning Sparser Neural Network with Differentiable Scale-Invariant Sparsity Measures Since most of the weight elements will be zero in the end, we only plot the histogram of nonzero weight elements for better observation

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:02:01.718637Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation c0e19583-af74-400d-977b-ec9f79cb5c74 · outbound

This paper cites Model Base acc Acc gain #FLOPs reduction Pruning-A (Li et al.,.

DeepHoyer: Learning Sparser Neural Network with Differentiable Scale-Invariant Sparsity Measures Model Base acc Acc gain #FLOPs reduction Pruning-A (Li et al.,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:02:01.687707Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation a82a4c2b-ff12-445c-a7a8-2e74ff0410f1 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

DeepHoyer: Learning Sparser Neural Network with Differentiable Scale-Invariant Sparsity Measures Adam: A Method for Stochastic Optimization

Reference 2009

Resolution: unresolved; no resolver link, observed 2026-08-14T11:02:01.366187Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8bcbfda1-cb84-463c-88a6-15dbc4126d65 · outbound

This paper cites Blind deconvolution using a normalized sparsity measure.

DeepHoyer: Learning Sparser Neural Network with Differentiable Scale-Invariant Sparsity Measures Blind deconvolution using a normalized sparsity measure

Reference 2014

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:02:01.837230Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 736d33fa-a6a5-4050-8b2c-9140cf34a430 · outbound

This paper cites Playing Atari with Deep Reinforcement Learning.

DeepHoyer: Learning Sparser Neural Network with Differentiable Scale-Invariant Sparsity Measures Playing Atari with Deep Reinforcement Learning

Reference 2015

Resolution: unresolved; no resolver link, observed 2026-08-14T11:02:01.391999Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5ff78d37-1891-4d6b-abe4-9d514a923aec · outbound

This paper cites Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding.

DeepHoyer: Learning Sparser Neural Network with Differentiable Scale-Invariant Sparsity Measures Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding

Reference 2016

Resolution: unresolved; no resolver link, observed 2026-08-14T11:02:01.355019Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d44a482f-51c2-4280-aeb7-6c7ee1e0018b · outbound

This paper cites NeST: A Neural Network Synthesis Tool Based on a Grow-and-Prune Paradigm.

DeepHoyer: Learning Sparser Neural Network with Differentiable Scale-Invariant Sparsity Measures NeST: A Neural Network Synthesis Tool Based on a Grow-and-Prune Paradigm

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-14T11:02:01.344633Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3f1953ef-ed8d-407a-931c-e4e36f514b82 · outbound

This paper cites Learning structured sparsity in deep neural networks.

DeepHoyer: Learning Sparser Neural Network with Differentiable Scale-Invariant Sparsity Measures Learning structured sparsity in deep neural networks

Reference 2018

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:02:01.806452Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation b8bdbc8d-6533-4c30-91b3-a7d9b62514d4 · outbound

This paper cites A method for ﬁnding structured sparse solutions to nonnegative least squares problems with applications.

DeepHoyer: Learning Sparser Neural Network with Differentiable Scale-Invariant Sparsity Measures A method for ﬁnding structured sparse solutions to nonnegative least squares problems with applications

Reference 2019

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:02:01.852536Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Pith citing papers

Observation b79f683b-ca43-4db2-98d2-31bc3cd6321c · inbound

Sparse-Reg: Improving Sample Complexity in Offline Reinforcement Learning using Sparsity cites this paper.

Sparse-Reg: Improving Sample Complexity in Offline Reinforcement Learning using Sparsity DeepHoyer: Learning Sparser Neural Network with Differentiable Scale-Invariant Sparsity Measures

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-15T19:14:53.759102Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e1a6acb3-2ed2-4390-8ea3-d2883182c58b · inbound

Extracting Governing Equations from Latent Dynamics via Multi-View Contrastive Learning cites this paper.

Extracting Governing Equations from Latent Dynamics via Multi-View Contrastive Learning DeepHoyer: Learning Sparser Neural Network with Differentiable Scale-Invariant Sparsity Measures

Reference 42

Resolution: verified exact; arxiv_id, observed 2026-06-27T07:30:40.907482Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.