Paper Citation Record · LEDGER

Set-Valued Sensitivity Analysis of Deep Neural Networks

As of 19 August 2026, this Paper Citation Record lists 22 of 22 outbound references and 0 inbound Pith citation observations for arXiv:2412.11057.

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

pith.paper-citation-record.v1
2412.11057 v1

Coverage vector

measured 22 of 22 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T15:26:11.017447Z

measured 22 of 22 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

22 of 22 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 0391af9a-fc2d-4246-ac2a-0e170bc88001 · outbound

This paper cites Second-order stochastic optimization for machine learn- ing in linear time.

Set-Valued Sensitivity Analysis of Deep Neural Networks Second-order stochastic optimization for machine learn- ing in linear time

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:26:11.416902Z

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Observation 8ac57eb6-bb91-4191-912f-83bd7fe12ff6 · outbound

This paper cites Loss surface sim- plexes for mode connecting volumes and fast ensembling.

Set-Valued Sensitivity Analysis of Deep Neural Networks Loss surface sim- plexes for mode connecting volumes and fast ensembling

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:26:11.396513Z

Source-reported events for the cited work

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Observation a44909a1-33f9-4f5a-b84c-c055c6fe3956 · outbound

This paper cites On robustness properties of convex risk minimization methods for pattern recognition.

Set-Valued Sensitivity Analysis of Deep Neural Networks On robustness properties of convex risk minimization methods for pattern recognition

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:26:11.377623Z

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Observation a2952817-61cb-458c-b18b-f9bb83980a58 · outbound

This paper cites Global minima of overparameterized neural networks.

Set-Valued Sensitivity Analysis of Deep Neural Networks Global minima of overparameterized neural networks

Reference 4

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Observation ada72f72-25ae-40ee-bb13-3ae06d349a3a · outbound

This paper cites Characterizations of strong regularity for variational inequal- ities over polyhedral convex sets.

Set-Valued Sensitivity Analysis of Deep Neural Networks Characterizations of strong regularity for variational inequal- ities over polyhedral convex sets

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:26:11.342763Z

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Observation 59a0340b-fa27-49a0-ac43-e95fbae7db5b · outbound

This paper cites Implicit functions and solution mappings , volume 543.

Set-Valued Sensitivity Analysis of Deep Neural Networks Implicit functions and solution mappings , volume 543

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:26:11.324519Z

Source-reported events for the cited work

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Observation 2f6af536-3fdf-4ffd-b14c-a6ed730db9e8 · outbound

This paper cites Efficient and accurate estimation of lipschitz constants for deep neural networks.

Set-Valued Sensitivity Analysis of Deep Neural Networks Efficient and accurate estimation of lipschitz constants for deep neural networks

Reference 7

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Source-reported events for the cited work

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Observation cd1caa95-b0f4-40ff-b2d6-8098425d8373 · outbound

This paper cites Introduction to sensitivity and stability analysis in nonlinear programming.

Set-Valued Sensitivity Analysis of Deep Neural Networks Introduction to sensitivity and stability analysis in nonlinear programming

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:26:11.294849Z

Source-reported events for the cited work

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Observation ad339921-9236-4136-9c56-8b6bf63723c5 · outbound

This paper cites Deep residual learning for image recognition.

Set-Valued Sensitivity Analysis of Deep Neural Networks Deep residual learning for image recognition

Reference 9

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Source-reported events for the cited work

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Observation 15dc4c77-58f0-4f04-a2a7-c30972fedb16 · outbound

This paper cites Understanding black-box predictions via influence functions.

Set-Valued Sensitivity Analysis of Deep Neural Networks Understanding black-box predictions via influence functions

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:26:11.265994Z

Source-reported events for the cited work

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Observation 9740085d-2ef9-4bea-b104-9e214b30b091 · outbound

This paper cites Robust statistics—the approach based on influence functions, 1986.

Set-Valued Sensitivity Analysis of Deep Neural Networks Robust statistics—the approach based on influence functions, 1986

Reference 11

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Observation ca06be27-65a5-45a2-99ab-6efa7ce62a1b · outbound

This paper cites Visualizing the loss landscape of neural nets.

Set-Valued Sensitivity Analysis of Deep Neural Networks Visualizing the loss landscape of neural nets

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-11T15:26:10.961549Z

Source-reported events for the cited work

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Observation cb4e0d1a-bd14-4852-a7c7-d9991dfd655f · outbound

This paper cites Using machine teaching to identify optimal training-set attacks on machine learners.

Set-Valued Sensitivity Analysis of Deep Neural Networks Using machine teaching to identify optimal training-set attacks on machine learners

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:26:11.225710Z

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 2b1b7315-1171-4202-8d21-f7d4769b0592 · outbound

This paper cites Variational analysis and generalized differentiation II: Applications, volume 331.

Set-Valued Sensitivity Analysis of Deep Neural Networks Variational analysis and generalized differentiation II: Applications, volume 331

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:26:11.208220Z

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 b86f3494-27c5-4933-b3f1-129c1d4b4cd7 · outbound

This paper cites Towards poisoning of deep learning algorithms with back-gradient optimization.

Set-Valued Sensitivity Analysis of Deep Neural Networks Towards poisoning of deep learning algorithms with back-gradient optimization

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:26:11.189210Z

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 e145a6a8-e9f8-4abf-b689-bf8c713cf8c4 · outbound

This paper cites The memory-perturbation equation: Understanding model’s sensitivity to data.

Set-Valued Sensitivity Analysis of Deep Neural Networks The memory-perturbation equation: Understanding model’s sensitivity to data

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:26:11.171646Z

Source-reported events for the cited work

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Observation ff0db937-f533-4935-8f46-567f5dcd16e1 · outbound

This paper cites Fast exact multiplication by the hessian.

Set-Valued Sensitivity Analysis of Deep Neural Networks Fast exact multiplication by the hessian

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:26:11.154715Z

Source-reported events for the cited work

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Observation 5ff3faaa-d509-4991-81a8-9f6384ae2d22 · outbound

This paper cites Springer Science & Business Media, 2009.

Set-Valued Sensitivity Analysis of Deep Neural Networks Springer Science & Business Media, 2009

Reference 18

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Source-reported events for the cited work

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Observation 0022e722-c1e7-4340-bf37-e7cf67370941 · outbound

This paper cites Model-targeted poisoning attacks with provable convergence.

Set-Valued Sensitivity Analysis of Deep Neural Networks Model-targeted poisoning attacks with provable convergence

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:26:11.123653Z

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 11844610-89b0-4440-862d-ea7cc5bcac03 · outbound

This paper cites Lipschitz regularity of deep neural networks: analysis and efficient estimation.

Set-Valued Sensitivity Analysis of Deep Neural Networks Lipschitz regularity of deep neural networks: analysis and efficient estimation

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-11T15:26:11.006004Z

Source-reported events for the cited work

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Observation ab3a89c9-7ced-48c1-b2b5-8dcf3a2ff94a · outbound

This paper cites Evaluating the Robustness of Neural Networks: An Extreme Value Theory Approach.

Set-Valued Sensitivity Analysis of Deep Neural Networks Evaluating the Robustness of Neural Networks: An Extreme Value Theory Approach

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-11T15:26:11.011765Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 38ec9770-7b51-41b8-9961-73ac32ca04bd · outbound

This paper cites HY k=h+1 W (k)⊤ diag(1(σ(W (k)xk−1 i ) > 0)) # ax(h−1) i ⊤ , (35) Rd ∋ ∂f (xi, w) ∂x(k) =.

Set-Valued Sensitivity Analysis of Deep Neural Networks HY k=h+1 W (k)⊤ diag(1(σ(W (k)xk−1 i ) > 0)) # ax(h−1) i ⊤ , (35) Rd ∋ ∂f (xi, w) ∂x(k) =

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:26:11.086359Z

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

No inbound Pith citation observations are available.