Lipschitz Optimization for Formal Verification of Homographies | Paper Citation Record

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This paper cites Roadmap for artificial in- telligence safety assurance.

Lipschitz Optimization for Formal Verification of Homographies Roadmap for artificial in- telligence safety assurance

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:57:02.277298Z

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This paper cites EASA concept pa- per: Guidance for level 1 & 2 machine-learning applications.

Lipschitz Optimization for Formal Verification of Homographies EASA concept pa- per: Guidance for level 1 & 2 machine-learning applications

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:57:02.258834Z

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This paper cites The sample complexities of global Lipschitz opti- mization.

Lipschitz Optimization for Formal Verification of Homographies The sample complexities of global Lipschitz opti- mization

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:57:02.247270Z

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This paper cites The Second International Verification of Neural Networks Competition (VNN-COMP 2021): Summary and Results.

Lipschitz Optimization for Formal Verification of Homographies The Second International Verification of Neural Networks Competition (VNN-COMP 2021): Summary and Results

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-25T05:00:22.278321Z

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This paper cites Neural network based runway landing guidance for general aviation au- toland.

Lipschitz Optimization for Formal Verification of Homographies Neural network based runway landing guidance for general aviation au- toland

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:57:02.273807Z

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This paper cites Certifying geometric ro- bustness of neural networks.

Lipschitz Optimization for Formal Verification of Homographies Certifying geometric ro- bustness of neural networks

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:57:02.254389Z

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This paper cites Verification of geometric robustness of neural networks via piecewise linear approx- imation and Lipschitz optimisation.

Lipschitz Optimization for Formal Verification of Homographies Verification of geometric robustness of neural networks via piecewise linear approx- imation and Lipschitz optimisation

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:57:02.280659Z

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Observation 6c37bfb7-d146-46a9-bffb-69c2af87c822 · outbound

This paper cites Efficient verification of ReLU- based neural networks via dependency analysis.

Lipschitz Optimization for Formal Verification of Homographies Efficient verification of ReLU- based neural networks via dependency analysis

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:57:02.269977Z

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Observation 9de35ddf-b0ea-40fa-a3bd-81e70abd0cd5 · outbound

This paper cites The fourth international verification of neural net- works competition (VNN-COMP 2023): Summary and re- sults.

Lipschitz Optimization for Formal Verification of Homographies The fourth international verification of neural net- works competition (VNN-COMP 2023): Summary and re- sults

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:57:02.243237Z

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This paper cites The right (angled) perspective: Improving the understanding of road scenes using boosted inverse perspective mapping.

Lipschitz Optimization for Formal Verification of Homographies The right (angled) perspective: Improving the understanding of road scenes using boosted inverse perspective mapping

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:57:02.283980Z

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Observation a5057fd3-6713-4361-9d2e-0a07edffde83 · outbound

This paper cites Homography-based state estimation for autonomous UA V landing.

Lipschitz Optimization for Formal Verification of Homographies Homography-based state estimation for autonomous UA V landing

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:57:02.313684Z

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Observation c920f293-3c5e-4d79-b34e-95446d4c4032 · outbound

This paper cites Real-time geometry-aware augmented reality in minimally invasive surgery.Healthcare technology letters, 4(5):163–167.

Lipschitz Optimization for Formal Verification of Homographies Real-time geometry-aware augmented reality in minimally invasive surgery.Healthcare technology letters, 4(5):163–167

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:57:02.290578Z

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This paper cites Position: Towards Resilience Against Adversarial Examples.

Lipschitz Optimization for Formal Verification of Homographies Position: Towards Resilience Against Adversarial Examples

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-05-25T05:00:22.272737Z

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Observation cb955591-9938-4605-9f66-7263fbf8ceb3 · outbound

This paper cites LARD - Landing Approach Runway Detection - Dataset for Vision Based Landing.

Lipschitz Optimization for Formal Verification of Homographies LARD - Landing Approach Runway Detection - Dataset for Vision Based Landing

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:57:02.287072Z

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Observation 352c899c-4190-4f3d-b6c0-e9b913157def · outbound

This paper cites Robustness of Rotation-Equivariant Networks to Adversarial Perturbations.

Lipschitz Optimization for Formal Verification of Homographies Robustness of Rotation-Equivariant Networks to Adversarial Perturbations

Reference 15

Resolution: verified exact; local_arxiv, observed 2026-05-25T05:00:22.266815Z

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Observation 26341140-4c16-49de-b04d-c4f48dea5fa6 · outbound

This paper cites Exploring the landscape of spatial robustness.

Lipschitz Optimization for Formal Verification of Homographies Exploring the landscape of spatial robustness

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:57:02.230955Z

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Observation 743f95c8-331d-47a9-8c04-567ea2772895 · outbound

This paper cites The robustness of deep networks: A ge- ometrical perspective.IEEE Signal Processing Magazine, 34(6):50–62.

Lipschitz Optimization for Formal Verification of Homographies The robustness of deep networks: A ge- ometrical perspective.IEEE Signal Processing Magazine, 34(6):50–62

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:57:02.234759Z

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Observation 6f24f95b-1605-4e10-9d29-d5d829aa4900 · outbound

This paper cites Fuzz testing based data augmentation to improve robustness of deep neural networks.

Lipschitz Optimization for Formal Verification of Homographies Fuzz testing based data augmentation to improve robustness of deep neural networks

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:57:02.238348Z

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Observation e9bd4b8c-c976-488b-87bb-017586f36599 · outbound

This paper cites Explaining and harnessing adversarial examples.

Lipschitz Optimization for Formal Verification of Homographies Explaining and harnessing adversarial examples

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:57:02.262955Z

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Observation ad43252b-42fd-4872-abc0-d87c6a132053 · outbound

This paper cites Efficient verifica- tion of neural networks against LVM-based specifications.

Lipschitz Optimization for Formal Verification of Homographies Efficient verifica- tion of neural networks against LVM-based specifications

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:57:02.250594Z

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Observation 20d430d3-9f50-4e80-be38-e5fc15f80466 · outbound

This paper cites Cambridge University Press.

Lipschitz Optimization for Formal Verification of Homographies Cambridge University Press

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:57:02.266281Z

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Observation c136f3f4-0e54-43ad-9b77-656d72b731f1 · outbound

This paper cites Towards compositional adversarial robustness: Generalizing adversarial training to composite semantic perturbations.

Lipschitz Optimization for Formal Verification of Homographies Towards compositional adversarial robustness: Generalizing adversarial training to composite semantic perturbations

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:57:02.305297Z

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Observation 24caefb5-13c7-4509-a326-b539f623ebcd · outbound

This paper cites Robustness certification of visual perception models via camera motion smoothing.

Lipschitz Optimization for Formal Verification of Homographies Robustness certification of visual perception models via camera motion smoothing

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:57:02.388741Z

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Observation 3cf25dd0-c4c0-4ce0-baa9-babe76b04257 · outbound

This paper cites Robustness ver- ification for perception models against camera motion per- turbations.

Lipschitz Optimization for Formal Verification of Homographies Robustness ver- ification for perception models against camera motion per- turbations

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:57:02.396242Z

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Observation c2b77a4d-f6ba-4b75-8fcf-1ad986e8b862 · outbound

This paper cites Pixel-wise smoothing for certified robustness against camera motion perturbations.

Lipschitz Optimization for Formal Verification of Homographies Pixel-wise smoothing for certified robustness against camera motion perturbations

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:57:02.403449Z

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Observation 3b5c531c-4520-4ff6-a25e-b57bdbf47fd6 · outbound

This paper cites When deep learning meets polyhedral theory: A sur- vey.INFORMS Journal on Computing.

Lipschitz Optimization for Formal Verification of Homographies When deep learning meets polyhedral theory: A sur- vey.INFORMS Journal on Computing

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:57:02.385414Z

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Observation a2364f73-e1d1-471d-b5ef-2492084dffb6 · outbound

This paper cites Towards Generalized Certified Robustness with Multi-Norm Training.

Lipschitz Optimization for Formal Verification of Homographies Towards Generalized Certified Robustness with Multi-Norm Training

Reference 27

Resolution: verified exact; local_arxiv, observed 2026-05-25T05:00:22.283759Z

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Observation 647c1de3-dd56-4bdd-b0b0-9186e198f68e · outbound

This paper cites Geometric robustness of deep networks: analysis and improvement.

Lipschitz Optimization for Formal Verification of Homographies Geometric robustness of deep networks: analysis and improvement

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:57:02.377796Z

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Observation 71b2ed40-aa72-4991-8fff-dcbfb07ad764 · outbound

This paper cites Reluplex: An efficient SMT solver for verifying deep neural networks.

Lipschitz Optimization for Formal Verification of Homographies Reluplex: An efficient SMT solver for verifying deep neural networks

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:57:02.381532Z

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Observation 0b8fcea0-3fbe-463d-a18f-e207dc1ab86f · outbound

This paper cites The 6th international verification of neural networks competition (VNN-COMP 2025): Summary and results.

Lipschitz Optimization for Formal Verification of Homographies The 6th international verification of neural networks competition (VNN-COMP 2025): Summary and results

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-05-25T05:00:22.255333Z

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Observation 3d7e6174-46c0-4a14-8374-a553ffd0ba72 · outbound

This paper cites Formal Verification of CNN-based Perception Systems.

Lipschitz Optimization for Formal Verification of Homographies Formal Verification of CNN-based Perception Systems

Reference 31

Resolution: verified exact; local_arxiv, observed 2026-05-25T05:00:22.261617Z

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Observation ff029d6b-d760-4185-af25-ac18a32a7b01 · outbound

This paper cites Deep learning.Nature, 521(7553):436–444.

Lipschitz Optimization for Formal Verification of Homographies Deep learning.Nature, 521(7553):436–444

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:57:02.406645Z

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Observation 2f44c39a-3779-4c81-aeb2-8cbe08c1bba3 · outbound

This paper cites SoK: Certified robustness for deep neural networks.

Lipschitz Optimization for Formal Verification of Homographies SoK: Certified robustness for deep neural networks

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:57:02.353187Z

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Observation ad18fb52-af84-4b67-b1de-654c178b8446 · outbound

This paper cites Al- gorithms for verifying deep neural networks.Foundations and Trends in Optimization, 4(3-4):244–404.

Lipschitz Optimization for Formal Verification of Homographies Al- gorithms for verifying deep neural networks.Foundations and Trends in Optimization, 4(3-4):244–404

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:57:02.367903Z

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Observation c74a9e7f-02cc-44b6-b13d-9c14a660d9cd · outbound

This paper cites Vision-centric BEV perception: A survey.IEEE TPAMI.

Lipschitz Optimization for Formal Verification of Homographies Vision-centric BEV perception: A survey.IEEE TPAMI

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:57:02.410189Z

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Observation 6ee41bad-09a6-424a-a083-ddc29cf8a220 · outbound

This paper cites Global optimization of Lipschitz functions.

Lipschitz Optimization for Formal Verification of Homographies Global optimization of Lipschitz functions

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:57:02.450046Z

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Observation 1b82ae8b-4b7a-483b-a19b-72b7cd6c8cd3 · outbound

This paper cites Is Certifying $\ell_p$ Robustness Still Worthwhile?.

Lipschitz Optimization for Formal Verification of Homographies Is Certifying $\ell_p$ Robustness Still Worthwhile?

Reference 37

Resolution: verified exact; arxiv_id, observed 2026-05-25T05:00:22.234821Z

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Observation da4df1a6-2e18-46ac-8491-9fa6da1ef99d · outbound

This paper cites Universal adversarial perturba- tions.

Lipschitz Optimization for Formal Verification of Homographies Universal adversarial perturba- tions

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:57:02.341986Z

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Observation 01446bfc-36b7-4387-a579-a8dcdb5767a8 · outbound

This paper cites Moss, Mykel J.

Lipschitz Optimization for Formal Verification of Homographies Moss, Mykel J

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:57:02.335246Z

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Observation e95654b4-050d-4fd4-ad32-3a88c8eeb7cd · outbound

This paper cites Reachability analysis of deep neural networks with provable guarantees.

Lipschitz Optimization for Formal Verification of Homographies Reachability analysis of deep neural networks with provable guarantees

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:57:02.338577Z

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Observation bcca549c-bef4-4c0e-a5b6-77b2cd3547b2 · outbound

This paper cites Landing system development based on inverse homography range camera fu- sion (IHRCF).Sensors, 22(5):1870.

Lipschitz Optimization for Formal Verification of Homographies Landing system development based on inverse homography range camera fu- sion (IHRCF).Sensors, 22(5):1870

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:57:02.332088Z

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Observation 80190778-64f0-4691-b2fe-c467e7e8e52f · outbound

This paper cites Neural network verification with branch-and-bound for general nonlinearities.

Lipschitz Optimization for Formal Verification of Homographies Neural network verification with branch-and-bound for general nonlinearities

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:57:02.328491Z

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Observation 9aec5a05-9a3a-4027-816a-15c7b74a053c · outbound

This paper cites An abstract domain for certifying neural networks.

Lipschitz Optimization for Formal Verification of Homographies An abstract domain for certifying neural networks

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:57:02.345775Z

Source-reported events for the cited work

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Observation ef9cc49c-c950-4b3b-b723-9ffa61335002 · outbound

This paper cites Certifying Some Distributional Robustness with Principled Adversarial Training.

Lipschitz Optimization for Formal Verification of Homographies Certifying Some Distributional Robustness with Principled Adversarial Training

Reference 44

Resolution: verified exact; arxiv_id, observed 2026-05-25T05:00:22.240908Z

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.

Observation f8f3badf-61eb-43c6-bbf5-47d1d9249ad5 · outbound

This paper cites In- triguing properties of neural networks.

Lipschitz Optimization for Formal Verification of Homographies In- triguing properties of neural networks

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:57:02.446430Z

Source-reported events for the cited work

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Observation a14799e7-5efa-4cb1-b4a2-ed09168e9b13 · outbound

This paper cites A new technique for fully autonomous and efficient 3D robotics hand/eye calibra- tion.IEEE Transactions on Robotics and Automation, 5(3): 345–358.

Lipschitz Optimization for Formal Verification of Homographies A new technique for fully autonomous and efficient 3D robotics hand/eye calibra- tion.IEEE Transactions on Robotics and Automation, 5(3): 345–358

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:57:02.297736Z

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.

Observation fd0bd4e6-99ae-4197-9fe7-a572cf16929a · outbound

This paper cites To- wards verifying the geometric robustness of large-scale neu- ral networks.Proceedings of the AAAI conference on AI.

Lipschitz Optimization for Formal Verification of Homographies To- wards verifying the geometric robustness of large-scale neu- ral networks.Proceedings of the AAAI conference on AI

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:57:02.301426Z

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Observation 13db431d-d913-4570-9bcb-b17e1e6ee529 · outbound

This paper cites Art-point: Im- proving rotation robustness of point cloud classifiers via ad- versarial rotation.

Lipschitz Optimization for Formal Verification of Homographies Art-point: Im- proving rotation robustness of point cloud classifiers via ad- versarial rotation

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:57:02.309898Z

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Observation 147cf946-da7e-4cd1-adfe-f4bd211d003a · outbound

This paper cites Beta-CROWN: Efficient bound propagation with per-neuron split constraints for com- plete and incomplete neural network verification.NeurIPS, 34.

Lipschitz Optimization for Formal Verification of Homographies Beta-CROWN: Efficient bound propagation with per-neuron split constraints for com- plete and incomplete neural network verification.NeurIPS, 34

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:57:02.324718Z

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Observation ff47aa0f-e154-4fed-ba5e-1ce16159b25b · outbound

This paper cites Deobfuscating machine learning assurance and approval.

Lipschitz Optimization for Formal Verification of Homographies Deobfuscating machine learning assurance and approval

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:57:02.293928Z

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.

Observation 4e73e125-9692-4db8-9a6b-9ff30c2929eb · outbound

This paper cites Toward certified ro- bustness against real-world distribution shifts.

Lipschitz Optimization for Formal Verification of Homographies Toward certified ro- bustness against real-world distribution shifts

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:57:02.317471Z

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.

Observation 9e1129b2-5654-434d-9837-99c54f3851b9 · outbound

This paper cites Marabou 2.0: a versatile formal analyzer of neural networks.

Lipschitz Optimization for Formal Verification of Homographies Marabou 2.0: a versatile formal analyzer of neural networks

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:57:02.321146Z

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.

Observation 10512bd6-a29a-46c1-a902-caa8bc8745ec · outbound

This paper cites Spatially Transformed Adversarial Examples.

Lipschitz Optimization for Formal Verification of Homographies Spatially Transformed Adversarial Examples

Reference 53

Resolution: verified exact; local_arxiv, observed 2026-05-25T05:00:22.289822Z

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.

Observation 6809214b-9aa0-41b0-b442-c29bb981d2fc · outbound

This paper cites Automatic perturbation analysis for scalable certified robustness and beyond.

Lipschitz Optimization for Formal Verification of Homographies Automatic perturbation analysis for scalable certified robustness and beyond

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:57:02.453523Z

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.

Observation 3c9b4827-c04e-4ff5-9bcd-382fae6f80f6 · outbound

This paper cites Fast and Complete: En- abling complete neural network verification with rapid and massively parallel incomplete verifiers.

Lipschitz Optimization for Formal Verification of Homographies Fast and Complete: En- abling complete neural network verification with rapid and massively parallel incomplete verifiers

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:57:02.438036Z

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.

Observation ab00a156-ff76-4557-b01e-4f2f2671db8d · outbound

This paper cites Provable defense against geometric transformations.

Lipschitz Optimization for Formal Verification of Homographies Provable defense against geometric transformations

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:57:02.432488Z

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.

Observation 33d32b05-c2f5-45a3-b94c-12cc165ba19c · outbound

This paper cites Efficient neural network robustness certi- fication with general activation functions.

Lipschitz Optimization for Formal Verification of Homographies Efficient neural network robustness certi- fication with general activation functions

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:57:02.421628Z

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.

Observation 6b2e97d3-1b6c-48c7-87f2-208124a89a25 · outbound

This paper cites General cutting planes for bound-propagation-based neural network verifica- tion.

Lipschitz Optimization for Formal Verification of Homographies General cutting planes for bound-propagation-based neural network verifica- tion

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:57:02.417811Z

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.

Observation a88ff804-d818-402a-a50e-621370f74e93 · outbound

This paper cites an unresolved cited work.

Lipschitz Optimization for Formal Verification of Homographies Unresolved cited work

Reference 59

Resolution: unresolved; raw_fallback, observed 2026-05-25T12:57:02.424943Z

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.

Observation 35b23dde-6a07-4386-9c50-6b7f1f1eafdc · outbound

This paper cites Sample images from each dataset.

Lipschitz Optimization for Formal Verification of Homographies Sample images from each dataset

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:57:02.428642Z

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.

Observation 4fe11547-cd9e-4437-b233-f2cdaaf0e412 · outbound

This paper cites In this case, bilinear interpolation relies on padding mechanisms to impute missing pixel values.

Lipschitz Optimization for Formal Verification of Homographies In this case, bilinear interpolation relies on padding mechanisms to impute missing pixel values

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:57:02.442968Z

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.

Observation c5f68c02-e9cb-4d9b-9b7b-b6d54fe963e1 · outbound

This paper cites an unresolved cited work.

Lipschitz Optimization for Formal Verification of Homographies Unresolved cited work

Reference 62

Resolution: malformed identifier; raw_fallback, observed 2026-05-25T12:57:02.392082Z

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.

Observation d652b99c-d8f4-41da-b353-09c5d3d22032 · outbound

This paper cites an unresolved cited work.

Lipschitz Optimization for Formal Verification of Homographies Unresolved cited work

Reference 63

Resolution: unresolved; raw_fallback, observed 2026-05-25T12:57:02.413678Z

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.

Observation 180eab68-87b1-4859-90d1-50bf4cdcebb4 · outbound

This paper cites In this context, t=0and Eq.

Lipschitz Optimization for Formal Verification of Homographies In this context, t=0and Eq

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:57:02.399677Z

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.

Observation 8059839b-48c2-463b-b9e1-902785547bcd · outbound

This paper cites an unresolved cited work.

Lipschitz Optimization for Formal Verification of Homographies Unresolved cited work

Reference 65

Resolution: unresolved; raw_fallback, observed 2026-05-25T12:57:02.364031Z

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.

Observation c2f099de-1a17-467e-bc61-c762577063e1 · outbound

This paper cites 13 and derive a majorant for the gradient of the inverse transform ∇⊤ ∆ψT −1 , more particularly along each coordinate by maximizing ∂u0 ∂∆ψ and ∂v0 ∂∆ψ independently.

Lipschitz Optimization for Formal Verification of Homographies 13 and derive a majorant for the gradient of the inverse transform ∇⊤ ∆ψT −1 , more particularly along each coordinate by maximizing ∂u0 ∂∆ψ and ∂v0 ∂∆ψ independently

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:57:02.357172Z

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.

Observation 2902f77e-6664-4fa1-bd9d-22933083e6df · outbound

This paper cites [7] proposes to usefbound =f κ1+κ2 2 + L 2 (κ2 −κ 1).

Lipschitz Optimization for Formal Verification of Homographies [7] proposes to usefbound =f κ1+κ2 2 + L 2 (κ2 −κ 1)

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:57:02.360742Z

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.

Observation dce77132-c4e9-43b7-9a0e-86a790169394 · outbound

This paper cites an unresolved cited work.

Lipschitz Optimization for Formal Verification of Homographies Unresolved cited work

Reference 68

Resolution: unresolved; raw_fallback, observed 2026-05-25T12:57:02.373546Z

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.

Observation b9b9524d-f298-4a93-b4ba-2ce42cb5bfba · outbound

This paper cites 2, this section presents extended robustness results on additional networks of the VNN-COMP benchmarks.

Lipschitz Optimization for Formal Verification of Homographies 2, this section presents extended robustness results on additional networks of the VNN-COMP benchmarks

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:57:02.349355Z

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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