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Paper Citation Record · LEDGER

Dying ReLU and Initialization: Theory and Numerical Examples

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 16 inbound Pith citation observations for arXiv:1903.06733.

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

pith.paper-citation-record.v1
1903.06733 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 16 of 16 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 16 of 16 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-14T04:29:35.202557Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T07:09:38.437806Z

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0 of 0 outbound references displayed

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Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 83e3d629-1fa3-4f97-b01d-6efcce177fd8 · inbound

DeepONet: Learning nonlinear operators for identifying differential equations based on the universal approximation theorem of operators cites this paper.

DeepONet: Learning nonlinear operators for identifying differential equations based on the universal approximation theorem of operators Dying ReLU and Initialization: Theory and Numerical Examples

Reference 16

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verified exact
arxiv_id, observed 2026-05-15T03:17:25.310784Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-15T03:17:25.281108Z digest=sha256:332cee47ab6ccded32c86b0954b38485329d01b8d9b42160efd39479765caa24

Observation ac65f711-2429-4858-a1e8-61772c298eb0 · inbound

Modelling Mosquito Population Dynamics using PINN-derived Empirical Parameters cites this paper.

Modelling Mosquito Population Dynamics using PINN-derived Empirical Parameters Dying ReLU and Initialization: Theory and Numerical Examples

Reference 44

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no resolver link, observed 2026-08-11T18:51:27.273673Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T18:51:27.273673Z digest=sha256:def13af443c3348482a29bf9faa57ee98e6d3b57b3a5dad8614646c704967cde

Observation 06227ee4-62f2-434a-a1d9-91c9bb513069 · inbound

Risk forecasting using Long Short-Term Memory Mixture Density Networks cites this paper.

Risk forecasting using Long Short-Term Memory Mixture Density Networks Dying ReLU and Initialization: Theory and Numerical Examples

Reference 47

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no resolver link, observed 2026-08-10T22:35:17.597382Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T22:35:17.597382Z digest=sha256:432d02b88061b20baff264aee3efa23fbc1169ffb04e377dd5555dc30ea79d3e

Observation 0e6062f9-d2ed-4555-9e91-8f8cfaf0f8b4 · inbound

How to warm-start your unfolding network cites this paper.

How to warm-start your unfolding network Dying ReLU and Initialization: Theory and Numerical Examples

Reference 37

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no resolver link, observed 2026-08-09T14:18:41.445166Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T14:18:41.445166Z digest=sha256:ee8cf4808c8088214e5eae7ca8cf0bff4a2b173857aee04656ebd8153ee6b6b0

Observation 44655a1b-e57b-4df3-9a57-4a12b0832b92 · inbound

STAR-Pose: Efficient Low-Resolution Video Human Pose Estimation via Spatial-Temporal Adaptive Super-Resolution cites this paper.

STAR-Pose: Efficient Low-Resolution Video Human Pose Estimation via Spatial-Temporal Adaptive Super-Resolution Dying ReLU and Initialization: Theory and Numerical Examples

Reference 20

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no resolver link, observed 2026-08-06T23:52:38.970034Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:52:38.970034Z digest=sha256:7848c5824a9b10e59cdeb7e163dc5fee3cce5c2957ac1b074078862c48881ffa

Observation d717e8d7-65e4-46d2-a40c-dc2188495c62 · inbound

TinyProto: Communication-Efficient Federated Learning with Sparse Prototypes in Resource-Constrained Environments cites this paper.

TinyProto: Communication-Efficient Federated Learning with Sparse Prototypes in Resource-Constrained Environments Dying ReLU and Initialization: Theory and Numerical Examples

Reference 16

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unresolved
no resolver link, observed 2026-08-06T19:58:04.270657Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:58:04.270657Z digest=sha256:51b5ffe2f26abb42527f8c081856cb44df1559fdcdb2c297896594ea4260da19

Observation 8a2f37cb-ecd2-4520-9ae7-3c96f4226fd0 · inbound

4D-MISR: A unified model for low-dose super-resolution imaging via feature fusion cites this paper.

4D-MISR: A unified model for low-dose super-resolution imaging via feature fusion Dying ReLU and Initialization: Theory and Numerical Examples

Reference 30

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no resolver link, observed 2026-08-06T17:49:30.173172Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:49:30.173172Z digest=sha256:78a3cea5f359e9d8e44a3526bc923cb94349ba840f05d4f5bd3419fb26eb4c5d

Observation df1e04ef-e002-4421-b7b4-dc71ddd32eed · inbound

Optimized Weight Initialization on the Stiefel Manifold for Deep ReLU Neural Networks cites this paper.

Optimized Weight Initialization on the Stiefel Manifold for Deep ReLU Neural Networks Dying ReLU and Initialization: Theory and Numerical Examples

Reference 19

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no resolver link, observed 2026-08-05T13:54:40.117887Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T13:54:40.117887Z digest=sha256:d15c70956e160aa9b77917e4dfeb9cd77b87d73f00b30db700550c3f60695a93

Observation ad8daf11-8d6c-4266-a6e0-e8e46ae36001 · inbound

Bug or Feature$^2$: Weight Drift, Activation Sparsity and Spikes cites this paper.

Bug or Feature$^2$: Weight Drift, Activation Sparsity and Spikes Dying ReLU and Initialization: Theory and Numerical Examples

Reference 37

Resolution
verified exact
arxiv_id, observed 2026-05-20T13:48:19.641175Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-05-20T13:46:32.405079Z digest=sha256:bff601061d17a2280eb0a5d7ff34f045916ebfdd5b05379df615da0dc9895401

Observation ca9507fc-f464-4af7-9f8c-3bd8038cb2a7 · inbound

Bug or Feature$^2$: Weight Drift, Activation Sparsity and Spikes cites this paper.

Bug or Feature$^2$: Weight Drift, Activation Sparsity and Spikes Dying ReLU and Initialization: Theory and Numerical Examples

Reference 37

Resolution
verified exact
arxiv_id, observed 2026-05-22T09:16:19.677693Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-05-22T09:15:32.395442Z digest=sha256:464f215cd8ac3b77ca75361d18e6cac68eb104825ed9e4007d69d3f8c4c616f4

Observation 42fc4e89-9e5c-40bf-840e-7b3a9af88f86 · inbound

Preserving Plasticity in Continual Learning via Dynamical Isometry cites this paper.

Preserving Plasticity in Continual Learning via Dynamical Isometry Dying ReLU and Initialization: Theory and Numerical Examples

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-07-03T00:07:28.515553Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 33f75801-431f-47ae-a5e9-74ad184df649 · inbound

NASDAQ: Normalized Observation Space Dynamics-Augmented Q-Learning cites this paper.

NASDAQ: Normalized Observation Space Dynamics-Augmented Q-Learning Dying ReLU and Initialization: Theory and Numerical Examples

Reference 52

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verified exact
arxiv_id, observed 2026-07-04T06:19:37.636482Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 6899582e-2e48-4637-884b-447fe454293f · inbound

Interpretable Material Spatial Intelligence for Discovery of Governing Microstructural Features cites this paper.

Interpretable Material Spatial Intelligence for Discovery of Governing Microstructural Features Dying ReLU and Initialization: Theory and Numerical Examples

Reference 96

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malformed identifier
arxiv_id, observed 2026-07-04T07:09:38.439286Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 8fc7cb80-1a3c-44a9-b455-23815fc39d53 · inbound

The Map Behind the Flow: Finite-Step Gradient Descent as a Dynamical System cites this paper.

The Map Behind the Flow: Finite-Step Gradient Descent as a Dynamical System Dying ReLU and Initialization: Theory and Numerical Examples

Reference 40

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no resolver link, observed 2026-07-11T10:24:00.719150Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-11T10:24:00.719150Z digest=sha256:ade21b3acb602f783e29a3b379b8c91fa4f6dadb03c9d14a213aa1783db99345

Observation 0e2487fa-eb6a-45b7-87ab-3c7e0e240e6a · inbound

A Counterexample to Fourier Alignment in Single-Neuron Modular Addition cites this paper.

A Counterexample to Fourier Alignment in Single-Neuron Modular Addition Dying ReLU and Initialization: Theory and Numerical Examples

Reference 11

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unresolved
no resolver link, observed 2026-08-08T18:34:18.323218Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T18:34:18.323218Z digest=sha256:94a3637a78ac47feb187033c65932abb1ea1eb178e558baef767257417c7a245

Observation ae3d2452-67f8-45ac-97c0-e854a20f3159 · inbound

Tevatron-Elastic: A Unified Abstraction for Training Elastic Retrievers and Rerankers cites this paper.

Tevatron-Elastic: A Unified Abstraction for Training Elastic Retrievers and Rerankers Dying ReLU and Initialization: Theory and Numerical Examples

Reference 32

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unresolved
no resolver link, observed 2026-08-14T04:29:35.202557Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T04:29:35.202557Z digest=sha256:a7af9892d2b45790b6a288f8b3a5d31697d624b060a7959ce2c1073fdd566edb