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Paper Citation Record · LEDGER

Provably-Safe Neural Network Training Using Hybrid Zonotope Reachability Analysis

As of 11 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 1 inbound Pith citation observation for arXiv:2501.13023.

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

pith.paper-citation-record.v1
2501.13023 v3

Coverage vector

measured 37 of 37 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T16:39:14.759719Z

measured 38 of 38 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-01T01:19:12.424654Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T13:05:44.274610Z

Reference resolution

37 of 37 outbound references displayed

  • verified exact1
  • verified fuzzy23
  • unresolved13
  • parse uncertain0
  • malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f65a25b8-2c66-4e7a-b99c-2a1ab0d655da · outbound

This paper cites Challenges of real-world reinforcement learning: definitions, benchmarks and analysis,.

Provably-Safe Neural Network Training Using Hybrid Zonotope Reachability Analysis Challenges of real-world reinforcement learning: definitions, benchmarks and analysis,

Reference 1

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation c01c97eb-06e9-4b8f-bea3-1f260c6acd8d · outbound

This paper cites Robust physical-world attacks on deep learning visual classification,.

Provably-Safe Neural Network Training Using Hybrid Zonotope Reachability Analysis Robust physical-world attacks on deep learning visual classification,

Reference 2

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 43076690-9623-4ec8-8866-bd19b6056914 · outbound

This paper cites A Review of Safe Reinforcement Learning: Methods, Theory and Applications.

Provably-Safe Neural Network Training Using Hybrid Zonotope Reachability Analysis A Review of Safe Reinforcement Learning: Methods, Theory and Applications

Reference 3

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 5e2f1b91-b65e-464e-b832-4249fcd4b507 · outbound

This paper cites Constrained decision transformer for offline safe reinforcement learning,.

Provably-Safe Neural Network Training Using Hybrid Zonotope Reachability Analysis Constrained decision transformer for offline safe reinforcement learning,

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation c2ecbe97-e62f-4ccb-81f5-39bb71bf37ca · outbound

This paper cites POLICE: Provably optimal linear constraint enforcement for deep neural networks,.

Provably-Safe Neural Network Training Using Hybrid Zonotope Reachability Analysis POLICE: Provably optimal linear constraint enforcement for deep neural networks,

Reference 5

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 076105ab-ee21-4b8a-ac17-64d0002859b6 · outbound

This paper cites Hybrid zonotopes exactly represent ReLU neural networks,.

Provably-Safe Neural Network Training Using Hybrid Zonotope Reachability Analysis Hybrid zonotopes exactly represent ReLU neural networks,

Reference 6

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation cd256108-f0ee-444c-87b6-7985fb3f4fc5 · outbound

This paper cites Open- and closed-loop neural network verification using polynomial zono- topes,.

Provably-Safe Neural Network Training Using Hybrid Zonotope Reachability Analysis Open- and closed-loop neural network verification using polynomial zono- topes,

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 240e2d9d-708c-4184-9bff-e0662879d8c2 · outbound

This paper cites Verification of deep convolutional neural networks using imagestars,.

Provably-Safe Neural Network Training Using Hybrid Zonotope Reachability Analysis Verification of deep convolutional neural networks using imagestars,

Reference 8

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation a2427baf-7f4a-4915-b906-472f5859c58c · outbound

This paper cites Verification of recurrent neural networks with star reachability,.

Provably-Safe Neural Network Training Using Hybrid Zonotope Reachability Analysis Verification of recurrent neural networks with star reachability,

Reference 9

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 12ab7f56-631a-492f-903e-a944bbb17b52 · outbound

This paper cites Lyapunov-stable neural-network control.

Provably-Safe Neural Network Training Using Hybrid Zonotope Reachability Analysis Lyapunov-stable neural-network control

Reference 10

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation d03e8bb9-dd6d-4a1c-8906-138393fe9516 · outbound

This paper cites Certified Robust Invariant Polytope Training in Neural Controlled ODEs.

Provably-Safe Neural Network Training Using Hybrid Zonotope Reachability Analysis Certified Robust Invariant Polytope Training in Neural Controlled ODEs

Reference 11

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 3f66a7d3-c1b4-48c1-8960-89aa861f2b09 · outbound

This paper cites Differentiable abstract interpretation for provably robust neural networks,.

Provably-Safe Neural Network Training Using Hybrid Zonotope Reachability Analysis Differentiable abstract interpretation for provably robust neural networks,

Reference 12

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation c92e052e-f4d3-4338-ae9a-042b457b299d · outbound

This paper cites an unresolved cited work.

Provably-Safe Neural Network Training Using Hybrid Zonotope Reachability Analysis Unresolved cited work

Reference 13

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unresolved
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation c6fc243c-1202-4837-83aa-6accc600d2d8 · outbound

This paper cites Provable defenses against adversarial ex- amples via the convex outer adversarial polytope,.

Provably-Safe Neural Network Training Using Hybrid Zonotope Reachability Analysis Provable defenses against adversarial ex- amples via the convex outer adversarial polytope,

Reference 14

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 0803a134-9758-4c46-896e-eb2d70b72ef2 · outbound

This paper cites Constrained Feedforward Neural Network Training via Reachability Analysis.

Provably-Safe Neural Network Training Using Hybrid Zonotope Reachability Analysis Constrained Feedforward Neural Network Training via Reachability Analysis

Reference 15

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unresolved
no resolver link, observed 2026-08-10T16:39:14.675069Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation efe1cf70-cbda-425f-a37d-81abbfbf3405 · outbound

This paper cites Neural network repair with reachability analysis,.

Provably-Safe Neural Network Training Using Hybrid Zonotope Reachability Analysis Neural network repair with reachability analysis,

Reference 16

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 3147175a-bcf4-4ce5-919f-ac88e48cdf3f · outbound

This paper cites Hybrid zonotopes: A new set representation for reachability analysis of mixed logical dynamical systems,.

Provably-Safe Neural Network Training Using Hybrid Zonotope Reachability Analysis Hybrid zonotopes: A new set representation for reachability analysis of mixed logical dynamical systems,

Reference 17

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 205007c3-ec71-40cf-8b1e-f4d40c3b06c2 · outbound

This paper cites Unions and complements of hybrid zonotopes,.

Provably-Safe Neural Network Training Using Hybrid Zonotope Reachability Analysis Unions and complements of hybrid zonotopes,

Reference 18

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 8470a841-3f85-4e70-b0b9-c32b5ce71888 · outbound

This paper cites zonoLAB: A MATLAB toolbox for set-based control systems anal- ysis using hybrid zonotopes,.

Provably-Safe Neural Network Training Using Hybrid Zonotope Reachability Analysis zonoLAB: A MATLAB toolbox for set-based control systems anal- ysis using hybrid zonotopes,

Reference 19

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 9608a2fd-20af-4051-8343-827ba78f556c · outbound

This paper cites Backward reachability analysis of neural feedback systems using hybrid zonotopes,.

Provably-Safe Neural Network Training Using Hybrid Zonotope Reachability Analysis Backward reachability analysis of neural feedback systems using hybrid zonotopes,

Reference 20

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation aa729b0b-1213-4d5e-92bf-079f5a43a291 · outbound

This paper cites A set-based approach for robust control co-design,.

Provably-Safe Neural Network Training Using Hybrid Zonotope Reachability Analysis A set-based approach for robust control co-design,

Reference 21

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 463947a3-e4c9-4b4a-9486-b76f26fa044d · outbound

This paper cites Hybrid Zonotope-Based Backward Reachability Analysis for Neural Feedback Systems With Nonlinear Plant Models,.

Provably-Safe Neural Network Training Using Hybrid Zonotope Reachability Analysis Hybrid Zonotope-Based Backward Reachability Analysis for Neural Feedback Systems With Nonlinear Plant Models,

Reference 22

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 857b3db1-c045-4c36-8a1f-b9d2f23f1950 · outbound

This paper cites Reachability analysis and safety verification of neural feedback systems via hybrid zonotopes,.

Provably-Safe Neural Network Training Using Hybrid Zonotope Reachability Analysis Reachability analysis and safety verification of neural feedback systems via hybrid zonotopes,

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T16:39:15.012001Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation c3dd1064-1c03-4e96-a416-b8f6ab99817d · outbound

This paper cites Scalable zonotopic under-approximation of backward reachable sets for uncertain linear systems,.

Provably-Safe Neural Network Training Using Hybrid Zonotope Reachability Analysis Scalable zonotopic under-approximation of backward reachable sets for uncertain linear systems,

Reference 24

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verified fuzzy
raw_fallback, observed 2026-08-10T16:39:14.998164Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation af690699-ca9b-4554-9155-0d74c3fbfe83 · outbound

This paper cites Presolve reductions in mixed integer programming,.

Provably-Safe Neural Network Training Using Hybrid Zonotope Reachability Analysis Presolve reductions in mixed integer programming,

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T16:39:14.984167Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 89578086-4193-438b-a239-769c724e6c57 · outbound

This paper cites Constrained zonotopes: A new tool for set-based estimation and fault detection,.

Provably-Safe Neural Network Training Using Hybrid Zonotope Reachability Analysis Constrained zonotopes: A new tool for set-based estimation and fault detection,

Reference 26

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no resolver link, observed 2026-08-10T16:39:14.717561Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T16:39:14.717561Z digest=sha256:ce97634ad17af6f456c7dff4825fd623edf004da6a0b487817f91096a43a2b0b

Observation 6e697969-f539-4462-97d0-017142f6b45b · outbound

This paper cites Pytorch: An imperative style, high-performance deep learning library,.

Provably-Safe Neural Network Training Using Hybrid Zonotope Reachability Analysis Pytorch: An imperative style, high-performance deep learning library,

Reference 27

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unresolved
no resolver link, observed 2026-08-10T16:39:14.721414Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation ae6b7ec5-61ae-4c26-b756-9d78fb7f346f · outbound

This paper cites Two-Stage Predict+ Optimize for MILPs with Unknown Parameters in Constraints,.

Provably-Safe Neural Network Training Using Hybrid Zonotope Reachability Analysis Two-Stage Predict+ Optimize for MILPs with Unknown Parameters in Constraints,

Reference 28

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verified fuzzy
raw_fallback, observed 2026-08-10T16:39:14.954416Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 0380415d-7e2c-44ac-bb87-2f4d357d652d · outbound

This paper cites Interior point solving for lp-based pre- diction+ optimisation,.

Provably-Safe Neural Network Training Using Hybrid Zonotope Reachability Analysis Interior point solving for lp-based pre- diction+ optimisation,

Reference 29

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verified fuzzy
raw_fallback, observed 2026-08-10T16:39:14.942167Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 598e9823-e56b-41ac-a742-fe21e1150c65 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Provably-Safe Neural Network Training Using Hybrid Zonotope Reachability Analysis Adam: A Method for Stochastic Optimization

Reference 30

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no resolver link, observed 2026-08-10T16:39:14.732970Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T16:39:14.732970Z digest=sha256:7f14a762bb78e7120f4f4df6728c12f8efba15872b50f45c27c1de2a26d2456c

Observation e040af23-70cb-4a48-bdc1-430b3dba3c34 · outbound

This paper cites Gurobi Optimization, Gurobi optimizer reference manual , 2021.

Provably-Safe Neural Network Training Using Hybrid Zonotope Reachability Analysis Gurobi Optimization, Gurobi optimizer reference manual , 2021

Reference 31

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raw_fallback, observed 2026-08-10T16:39:14.930400Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation e73346d6-75d8-49fe-bea7-a33012454b2f · outbound

This paper cites an unresolved cited work.

Provably-Safe Neural Network Training Using Hybrid Zonotope Reachability Analysis Unresolved cited work

Reference 32

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unresolved
no resolver link, observed 2026-08-10T16:39:14.741284Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T16:39:14.741284Z digest=sha256:02452f6e378b79674b4666dc14fdd7e73ebeea337f5280e4d6a349270ef99d7d

Observation a95fb6f6-a5ee-427f-a2ca-905c87fa6d9b · outbound

This paper cites Reachability analysis of nonlinear systems with uncertain parameters using conservative linearization,.

Provably-Safe Neural Network Training Using Hybrid Zonotope Reachability Analysis Reachability analysis of nonlinear systems with uncertain parameters using conservative linearization,

Reference 33

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verified fuzzy
raw_fallback, observed 2026-08-10T16:39:14.909790Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T16:39:14.744991Z digest=sha256:5520257429b62b2370f3824dd97f297361b08abbc7704198aba85c1e00d81423

Observation 0b73d7f4-24d1-47f9-8509-069ff034f25e · outbound

This paper cites Guaranteed Reach-Avoid for Black-Box Systems through Narrow Gaps via Neural Network Reachability.

Provably-Safe Neural Network Training Using Hybrid Zonotope Reachability Analysis Guaranteed Reach-Avoid for Black-Box Systems through Narrow Gaps via Neural Network Reachability

Reference 34

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local_arxiv, observed 2026-08-10T16:39:14.824890Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T16:39:14.748650Z digest=sha256:d28dc66beb23da3cf610dba16015f764f66872980e1d2fff3c2c93313f33fb3a

Observation 97f353f2-8859-4a27-974e-71b95edec22d · outbound

This paper cites Goal-Reaching Trajectory Design Near Danger with Piecewise Affine Reach-avoid Computation.

Provably-Safe Neural Network Training Using Hybrid Zonotope Reachability Analysis Goal-Reaching Trajectory Design Near Danger with Piecewise Affine Reach-avoid Computation

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-10T16:39:14.752222Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T16:39:14.752222Z digest=sha256:08f1c83dc4bf13124d6ae2ae57fb2eb9de6166a8a961471565c17e7b80438ea6

Observation fcbad085-483d-4bef-bb2b-9952034b2b64 · outbound

This paper cites Feurer and F.

Provably-Safe Neural Network Training Using Hybrid Zonotope Reachability Analysis Feurer and F

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T16:39:14.896741Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T16:39:14.756388Z digest=sha256:d0f93cfdafaf88fb23818cc502183ce9bbf952c83886f1975714a39d1d38ce21

Observation fec8ce34-dd53-400d-b7e3-f5d261adbcca · outbound

This paper cites Lyapunov-stable Neural Control for State and Output Feedback: A Novel Formulation.

Provably-Safe Neural Network Training Using Hybrid Zonotope Reachability Analysis Lyapunov-stable Neural Control for State and Output Feedback: A Novel Formulation

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-10T16:39:14.759719Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T16:39:14.759719Z digest=sha256:de723dfaac61416a509b25212810ad10302b37e549ae182d05c0c55635580aa1

Pith citing papers

Observation 54be8bad-4a9d-4032-8b0a-8f37b07fd2aa · inbound

ShardNet: Training Neural Controllers with Hard, Non-Convex Constraints cites this paper.

ShardNet: Training Neural Controllers with Hard, Non-Convex Constraints Provably-Safe Neural Network Training Using Hybrid Zonotope Reachability Analysis

Reference 6

Resolution
verified exact
arxiv_id, observed 2026-07-01T13:05:44.276129Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-07-01T01:19:12.424654Z digest=sha256:7e7e18163b17a70d44ff4a79499c9102762bcc65c95226a54a75cee16e335e46