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Paper Citation Record · LEDGER

Learning Neural Controllers with Optimality and Stability Guarantees Using Input-Output Dissipativity

As of 8 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 1 inbound Pith citation observation for arXiv:2506.06564.

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

pith.paper-citation-record.v1
2506.06564 v1

Coverage vector

measured 38 of 38 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T06:04:04.051199Z

measured 39 of 39 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-18T04:20:35.040577Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-18T04:20:51.963870Z

Reference resolution

38 of 38 outbound references displayed

  • verified exact1
  • verified fuzzy29
  • unresolved8
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 41a8d1e2-f36c-4b0d-aadf-3385472715c6 · outbound

This paper cites Deep reinforcement learning for robotics: A survey of real-world successes,.

Learning Neural Controllers with Optimality and Stability Guarantees Using Input-Output Dissipativity Deep reinforcement learning for robotics: A survey of real-world successes,

Reference 1

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 4a009553-97d7-4dfb-b844-912c3e998894 · outbound

This paper cites Deep reinforcement learning for intelligent transportation systems: A survey,.

Learning Neural Controllers with Optimality and Stability Guarantees Using Input-Output Dissipativity Deep reinforcement learning for intelligent transportation systems: A survey,

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T06:04:11.406409Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T06:03:59.222738Z digest=sha256:1f6dda7f940101e28a8a8f2fd99d62a9e11d34833076db07be903efdfa553655

Observation 65c99ca3-7fb2-4154-b691-08d23cdff7df · outbound

This paper cites Review on deep learning applications in frequency analysis and control of modern power system,.

Learning Neural Controllers with Optimality and Stability Guarantees Using Input-Output Dissipativity Review on deep learning applications in frequency analysis and control of modern power system,

Reference 3

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T06:03:59.343419Z digest=sha256:beb36abf86bb8da597aee87c8ba5d9d37d13ac324459a0dee43b9cdddfa8c090

Observation a3d55810-cc7e-434e-ac83-ffdc09cf2345 · outbound

This paper cites Sastry, Nonlinear systems: analysis, stability, and control , vol.

Learning Neural Controllers with Optimality and Stability Guarantees Using Input-Output Dissipativity Sastry, Nonlinear systems: analysis, stability, and control , vol

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T06:04:10.843549Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T06:03:59.442714Z digest=sha256:fa9688f6c78cd4182b3e27cd8fb418cc9a4f533c76c1bceea380ac9c9c9d136b

Observation 1e208f6d-544c-4375-b360-347d42d485f7 · outbound

This paper cites Approximate optimal controller synthesis for cart-poles and quadrotors via sums-of-squares,.

Learning Neural Controllers with Optimality and Stability Guarantees Using Input-Output Dissipativity Approximate optimal controller synthesis for cart-poles and quadrotors via sums-of-squares,

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T06:04:10.561783Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T06:03:59.615315Z digest=sha256:88531cd08860693a095f94085238a7dca385698c2853bc170cf879b74beb80aa

Observation db57a201-ae7e-4002-b802-b5b93d3a815b · outbound

This paper cites Convex synthesis and verification of control-lyapunov and barrier functions with input constraints,.

Learning Neural Controllers with Optimality and Stability Guarantees Using Input-Output Dissipativity Convex synthesis and verification of control-lyapunov and barrier functions with input constraints,

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T06:04:10.258774Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T06:03:59.737986Z digest=sha256:8031884ada7f5077364c78d7ae9b08818b4e783a0a2092ba1e831456d02ee7a7

Observation 6529bcc2-1d4b-49c2-92b6-d915acaaaac8 · outbound

This paper cites Advances in computational lyapunov analysis using sum-of-squares programming.,.

Learning Neural Controllers with Optimality and Stability Guarantees Using Input-Output Dissipativity Advances in computational lyapunov analysis using sum-of-squares programming.,

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T06:04:10.004896Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T06:03:59.850139Z digest=sha256:f849482f763cc8a86aae270249accec24a3707d6ff2bebbb7766c7950cbf75b2

Observation aba67a3b-5a0e-421b-9fc7-5359e52665cd · outbound

This paper cites On the construction of lyapunov functions using the sum of squares decomposition,.

Learning Neural Controllers with Optimality and Stability Guarantees Using Input-Output Dissipativity On the construction of lyapunov functions using the sum of squares decomposition,

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T06:04:09.677988Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T06:03:59.940721Z digest=sha256:a684ce97746d84bfc661941ba24e50223f3a641c3c7544800a35873259d83535

Observation 16064578-c3f9-4adc-a0fb-9ec8f94fa5a7 · outbound

This paper cites A globally asymptotically stable polynomial vector field with rational coefficients and no local polynomial lyapunov function,.

Learning Neural Controllers with Optimality and Stability Guarantees Using Input-Output Dissipativity A globally asymptotically stable polynomial vector field with rational coefficients and no local polynomial lyapunov function,

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T06:04:09.433452Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T06:04:00.138761Z digest=sha256:636365a955e70d70445157ec6548d3fb8442ca459d75ec5c10963ef212340cad

Observation 51004b0b-a4dd-4dc4-ac2e-1102e479a843 · outbound

This paper cites Neural lyapunov control of unknown nonlinear systems with stability guarantees,.

Learning Neural Controllers with Optimality and Stability Guarantees Using Input-Output Dissipativity Neural lyapunov control of unknown nonlinear systems with stability guarantees,

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T06:04:09.123361Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T06:04:00.262115Z digest=sha256:57ecd8dc7666d96e5b26e2cc30026a59e63fb9bd49281ea48cdcc105df851c26

Observation e3bc8421-070f-4541-bea2-66895893cdc6 · outbound

This paper cites Neural lyapunov control,.

Learning Neural Controllers with Optimality and Stability Guarantees Using Input-Output Dissipativity Neural lyapunov control,

Reference 11

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T06:04:00.372445Z digest=sha256:4adeb717dfca9cb87c3b0f92d6f4fdf56ff012210e32ca791f0d38eb6872dbfc

Observation 31d4f177-3ee0-4448-b354-b722ed20d982 · outbound

This paper cites Learning Lyapunov Functions for Piecewise Affine Systems with Neural Network Controllers.

Learning Neural Controllers with Optimality and Stability Guarantees Using Input-Output Dissipativity Learning Lyapunov Functions for Piecewise Affine Systems with Neural Network Controllers

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-07T06:04:00.514762Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T06:04:00.514762Z digest=sha256:0fa66860210660163f02af83c0ab5e7e357119f51ab7cca003235402e134fbf5

Observation c1e4dc84-672c-47c1-baf0-3477c701978f · outbound

This paper cites Lyapunov-stable neural-network control.

Learning Neural Controllers with Optimality and Stability Guarantees Using Input-Output Dissipativity Lyapunov-stable neural-network control

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-07T06:04:00.648334Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T06:04:00.648334Z digest=sha256:03972f1d2e3a0b21a9d27e3cea692399923e8e49f5dab6ce5e8f929581263b34

Observation 5a079352-7432-426a-9e16-3f7fb2ba3820 · outbound

This paper cites Lyapunov-stable neural control for state and output feedback: A novel formulation,.

Learning Neural Controllers with Optimality and Stability Guarantees Using Input-Output Dissipativity Lyapunov-stable neural control for state and output feedback: A novel formulation,

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T06:04:08.622264Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T06:04:00.802875Z digest=sha256:78b36e2092a694028443d6e3865ad40de2ef11d801c2e886f23aba881f6c1ec2

Observation fb08b07d-1141-4bd2-b242-5929d81ed1d4 · outbound

This paper cites Neural lyapunov control for discrete-time systems,.

Learning Neural Controllers with Optimality and Stability Guarantees Using Input-Output Dissipativity Neural lyapunov control for discrete-time systems,

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T06:04:08.317841Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T06:04:00.932527Z digest=sha256:6bbd0772ccba7bc704fab24967ce2ca20aadbae6fbe5b979113f20031ea8cb90

Observation 3c3480be-eff5-4b0e-b594-197ddd4c89d1 · outbound

This paper cites Counterexample guided inductive synthesis modulo theories,.

Learning Neural Controllers with Optimality and Stability Guarantees Using Input-Output Dissipativity Counterexample guided inductive synthesis modulo theories,

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T06:04:01.060719Z digest=sha256:bf6caa7465ee263f5e8a2229d29c6944c353aac1bcbf84157bcd7cdbefb6ccae

Observation b1707d3f-1784-41fc-a5f7-98b160095bd9 · outbound

This paper cites dreal: An smt solver for nonlinear theories over the reals,.

Learning Neural Controllers with Optimality and Stability Guarantees Using Input-Output Dissipativity dreal: An smt solver for nonlinear theories over the reals,

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T06:04:07.777326Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T06:04:01.184161Z digest=sha256:ae16221fe4ac82a8701fce09016710ba84bcc56817d5595e89d34e93e31aa46f

Observation bdd24d97-3053-4c02-83fa-33d062c8e570 · outbound

This paper cites Beta-crown: Efficient bound propagation with per-neuron split constraints for neural network robustness verification,.

Learning Neural Controllers with Optimality and Stability Guarantees Using Input-Output Dissipativity Beta-crown: Efficient bound propagation with per-neuron split constraints for neural network robustness verification,

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T06:04:07.473017Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T06:04:01.341632Z digest=sha256:cef176e3d1dd20677b7cfb424fd47af5370e27f448fffb168c181229ddc58a19

Observation 26cb99fa-922b-4abc-977b-55ff6126ddde · outbound

This paper cites Evaluating Robustness of Neural Networks with Mixed Integer Programming.

Learning Neural Controllers with Optimality and Stability Guarantees Using Input-Output Dissipativity Evaluating Robustness of Neural Networks with Mixed Integer Programming

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-07T06:04:01.503732Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T06:04:01.503732Z digest=sha256:a1d97a3cd5088599b83698c016f328a546a30a0065be17c397a48f409d1c541b

Observation 439bf41c-56ef-493b-8fdb-7642aad1427c · outbound

This paper cites Safety verification and robustness analysis of neural networks via quadratic constraints and semidefinite programming,.

Learning Neural Controllers with Optimality and Stability Guarantees Using Input-Output Dissipativity Safety verification and robustness analysis of neural networks via quadratic constraints and semidefinite programming,

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-07T06:04:01.611666Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T06:04:01.611666Z digest=sha256:70d874877e7fa7f9e8da830d3764228b65627117969fe1bf94801186cd03cb52

Observation b223bb63-8544-4c26-b01c-7422c8153077 · outbound

This paper cites Dissipative dynamical systems part i: General theory,.

Learning Neural Controllers with Optimality and Stability Guarantees Using Input-Output Dissipativity Dissipative dynamical systems part i: General theory,

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T06:04:07.268065Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T06:04:01.770187Z digest=sha256:6e25a741306710e803e55c6ca8a2bd5d9960bb525eb04d54320374c527892f17

Observation 50474a7b-d922-47e0-a653-96c329581ce2 · outbound

This paper cites Nonlinear regulator theory and an inverse optimal control problem,.

Learning Neural Controllers with Optimality and Stability Guarantees Using Input-Output Dissipativity Nonlinear regulator theory and an inverse optimal control problem,

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T06:04:07.039125Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T06:04:01.870610Z digest=sha256:f117e2a1c5749706a092511a2759a61bad931d07a688894b4e8434b2939fc4a4

Observation 9180f778-f6a3-480b-b02b-2631d75a64de · outbound

This paper cites Dissipativity and optimal control: Examining the turnpike phenomenon,.

Learning Neural Controllers with Optimality and Stability Guarantees Using Input-Output Dissipativity Dissipativity and optimal control: Examining the turnpike phenomenon,

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T06:04:06.796221Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T06:04:02.009444Z digest=sha256:7c0e53faabef4303a7b7e6697c93932db7207ccd06a9c9014eba125010867748

Observation d3612a99-288d-493e-b6d7-193911b76563 · outbound

This paper cites Nonlinear optimal control for stochastic dynamical systems,.

Learning Neural Controllers with Optimality and Stability Guarantees Using Input-Output Dissipativity Nonlinear optimal control for stochastic dynamical systems,

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T06:04:06.575784Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T06:04:02.183870Z digest=sha256:1fc7a2648adced9feb3fe52f89a2e934ae80f0814a1dadbda0f6396f715ac0af

Observation 32cc86f7-7989-46f8-8171-f9a9937aed29 · outbound

This paper cites Necessary and sufficient dissipativity- based conditions for feedback stabilization,.

Learning Neural Controllers with Optimality and Stability Guarantees Using Input-Output Dissipativity Necessary and sufficient dissipativity- based conditions for feedback stabilization,

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T06:04:06.323914Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T06:04:02.362408Z digest=sha256:d89f528671f5ad327cae4731ba54ccc53f26da7ff6ac4ccc6d2c484c8a27ee4d

Observation 178f2b7d-3df6-4f1e-8c93-8d04475a91b7 · outbound

This paper cites Compositional analysis of interconnected systems using delta dissipativity,.

Learning Neural Controllers with Optimality and Stability Guarantees Using Input-Output Dissipativity Compositional analysis of interconnected systems using delta dissipativity,

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T06:04:06.088928Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T06:04:02.474490Z digest=sha256:6424f6f19b181870a948d4abab34cf447e7e2a3e70f8bd9a4e8f63f85ad90479

Observation 11d4e2e8-9e12-4029-8721-0c61b853cfc6 · outbound

This paper cites Structured neural- pi control with end-to-end stability and output tracking guarantees,.

Learning Neural Controllers with Optimality and Stability Guarantees Using Input-Output Dissipativity Structured neural- pi control with end-to-end stability and output tracking guarantees,

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T06:04:05.849463Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T06:04:02.566925Z digest=sha256:01a00f987cfae825eae8b6c20f2c6e4e437e6c742b2c5b20fba989d017d755f6

Observation f7bd2cb4-8dfc-4dc9-9284-28d07c2c5de0 · outbound

This paper cites Synthesizing Neural Network Controllers with Closed-Loop Dissipativity Guarantees.

Learning Neural Controllers with Optimality and Stability Guarantees Using Input-Output Dissipativity Synthesizing Neural Network Controllers with Closed-Loop Dissipativity Guarantees

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-07T06:04:02.718356Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T06:04:02.718356Z digest=sha256:f2a47de64b269d3fa8db0e55f28a096ca38cee68faaff3f8fd07c2140b035fab

Observation bfc3d54b-27aa-4fc0-b1ab-316d1f419069 · outbound

This paper cites Learning dissipative neural dynamical systems,.

Learning Neural Controllers with Optimality and Stability Guarantees Using Input-Output Dissipativity Learning dissipative neural dynamical systems,

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T06:04:05.627563Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T06:04:02.858829Z digest=sha256:a61aa7ca5c9686b7e8805b81bfc493d3b7b3f80640b7fe16cb45f8d4f06318a6

Observation adad7d49-83f0-4e20-a2ac-23f79312be46 · outbound

This paper cites Learning chaotic dynamics in dissipative systems,.

Learning Neural Controllers with Optimality and Stability Guarantees Using Input-Output Dissipativity Learning chaotic dynamics in dissipative systems,

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T06:04:05.420662Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T06:04:03.007467Z digest=sha256:adaab6953c53e81fefe7ccf5625892c8ffe86d8d48c47c7adec676a2147d7910

Observation 1742c347-0796-4a4e-a296-5d24550fa016 · outbound

This paper cites Learning Deep Dissipative Dynamics.

Learning Neural Controllers with Optimality and Stability Guarantees Using Input-Output Dissipativity Learning Deep Dissipative Dynamics

Reference 31

Resolution
verified exact
local_arxiv, observed 2026-08-07T06:04:04.282300Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T06:04:03.115468Z digest=sha256:8c133afdc06a6923d5ef3a4e64b16003214e05b4e16139f0cb35fe11a50f3662

Observation a5a96ac5-aeb5-4c12-9f3d-5e4ec3c13f0f · outbound

This paper cites Sepulchre, M.

Learning Neural Controllers with Optimality and Stability Guarantees Using Input-Output Dissipativity Sepulchre, M

Reference 32

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no resolver link, observed 2026-08-07T06:04:03.252687Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T06:04:03.252687Z digest=sha256:754cafaa1f4e8c203ad1c8e128130b4ba7d0b14ad0000cc90c227f3b911c8ad9

Observation 01618e4c-efde-41e9-b1f7-9594a440092f · outbound

This paper cites Convex optimization,.

Learning Neural Controllers with Optimality and Stability Guarantees Using Input-Output Dissipativity Convex optimization,

Reference 33

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unresolved
no resolver link, observed 2026-08-07T06:04:03.345254Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T06:04:03.345254Z digest=sha256:4d5b35e1c0c81ee1695b59ed4e0f8698e9d57c5fcb10e6a0e1082103edb149d1

Observation 593b3958-a778-4bde-95b4-28dcd6a378af · outbound

This paper cites Towards Deep Learning Models Resistant to Adversarial Attacks.

Learning Neural Controllers with Optimality and Stability Guarantees Using Input-Output Dissipativity Towards Deep Learning Models Resistant to Adversarial Attacks

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-07T06:04:03.496726Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T06:04:03.496726Z digest=sha256:6d6409f89b87bc0b8d05db9b2550c14f7cb3e08b0538113dae0228ad398aa8f9

Observation 42d1436b-6f9e-42fc-9045-4a2c0f2d2ecd · outbound

This paper cites Direct parameterization of lipschitz-bounded deep networks,.

Learning Neural Controllers with Optimality and Stability Guarantees Using Input-Output Dissipativity Direct parameterization of lipschitz-bounded deep networks,

Reference 35

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verified fuzzy
raw_fallback, observed 2026-08-07T06:04:05.245292Z

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source=pdf_text observed=2026-08-07T06:04:03.666994Z digest=sha256:93cc454c3fab15fd88c71f6959a73bb892a7032705a852e050b5c46c649337b0

Observation 07e0f878-f3c0-4020-9990-e322982f71b3 · outbound

This paper cites Visioli, Practical PID control.

Learning Neural Controllers with Optimality and Stability Guarantees Using Input-Output Dissipativity Visioli, Practical PID control

Reference 36

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verified fuzzy
raw_fallback, observed 2026-08-07T06:04:05.037140Z

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source=pdf_text observed=2026-08-07T06:04:03.805151Z digest=sha256:08d87dc8c3535dc62fafcf0641fdb9c993297f506d499f9e19bee1531da7fd46

Observation 92cc2bc6-b07d-4eb6-b68d-6229293f8be6 · outbound

This paper cites Equilibrium-independent dissipativity with quadratic supply rates,.

Learning Neural Controllers with Optimality and Stability Guarantees Using Input-Output Dissipativity Equilibrium-independent dissipativity with quadratic supply rates,

Reference 37

Resolution
verified fuzzy
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source=pdf_text observed=2026-08-07T06:04:03.926110Z digest=sha256:a3b804539f7ab258c7aacc8fa04186dc56ffa989177e71f96e2ae614f6996ee4

Observation 63c25e45-641f-4ddd-9693-8a3aeca9f3c2 · outbound

This paper cites Global stabilization of polynomial systems using equilibrium-independent dissipativity,.

Learning Neural Controllers with Optimality and Stability Guarantees Using Input-Output Dissipativity Global stabilization of polynomial systems using equilibrium-independent dissipativity,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T06:04:04.537537Z

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source=pdf_text observed=2026-08-07T06:04:04.051199Z digest=sha256:e29f2ffdd730027101f9b5e12f40db20ac247459937b134ddd79bc257ec843a5

Pith citing papers

Observation 30debcf5-e98a-4731-ae9f-b63a2aef9b71 · inbound

Model-Free Power System Stability Enhancement with Dissipativity-Based Neural Control cites this paper.

Model-Free Power System Stability Enhancement with Dissipativity-Based Neural Control Learning Neural Controllers with Optimality and Stability Guarantees Using Input-Output Dissipativity

Reference 28

Resolution
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arxiv_id, observed 2026-07-02T02:17:13.031534Z

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source=pdf_text observed=2026-05-18T04:20:35.040577Z digest=sha256:120599f654c3d30aa318c2a7acc8b1e8ce151ae7caac6e4dc9514705d5f60784