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Efficient and Accurate Estimation of Lipschitz Constants for Deep Neural Networks

12 June 2019

George J. Pappas

Papers citing "Efficient and Accurate Estimation of Lipschitz Constants for Deep Neural Networks"

50 / 270 papers shown

Title
Hamiltonian Deep Neural Networks Guaranteeing Non-vanishing Gradients by Design C. Galimberti Luca Furieri Liang Xu Giancarlo Ferrari-Trecate 71 33 0 27 May 2021
LipBaB: Computing exact Lipschitz constant of ReLU networks Aritra Bhowmick Meenakshi D'Souza G. S. Raghavan 36 16 0 12 May 2021
ModelGuard: Runtime Validation of Lipschitz-continuous Models Taylor J. Carpenter Radoslav Ivanov Insup Lee James Weimer 18 3 0 30 Apr 2021
Analytical bounds on the local Lipschitz constants of ReLU networks Trevor Avant K. Morgansen FAtt 56 12 0 29 Apr 2021
Model Error Propagation via Learned Contraction Metrics for Safe Feedback Motion Planning of Unknown Systems Glen Chou N. Ozay Dmitry Berenson 100 25 0 18 Apr 2021
Orthogonalizing Convolutional Layers with the Cayley Transform Asher Trockman J. Zico Kolter 95 115 0 14 Apr 2021
Recurrent Equilibrium Networks: Flexible Dynamic Models with Guaranteed Stability and Robustness Max Revay Ruigang Wang I. Manchester 77 61 0 13 Apr 2021
Linear systems with neural network nonlinearities: Improved stability analysis via acausal Zames-Falb multipliers Patricia Pauli Dennis Gramlich J. Berberich Frank Allgöwer 43 27 0 31 Mar 2021
Learning Lipschitz Feedback Policies from Expert Demonstrations: Closed-Loop Guarantees, Generalization and Robustness Abed AlRahman Al Makdah Vishaal Krishnan Fabio Pasqualetti 29 0 0 30 Mar 2021
Understanding the role of importance weighting for deep learning Da Xu Yuting Ye Chuanwei Ruan FAtt 95 44 0 28 Mar 2021
CLIP: Cheap Lipschitz Training of Neural Networks Leon Bungert René Raab Tim Roith Leo Schwinn Daniel Tenbrinck 59 33 0 23 Mar 2021
Provably Correct Training of Neural Network Controllers Using Reachability Analysis Xiaowu Sun Yasser Shoukry 91 7 0 22 Feb 2021
Privacy-Preserving Kickstarting Deep Reinforcement Learning with Privacy-Aware Learners Parham Gohari Bo Chen Bo Wu Matthew T. Hale Ufuk Topcu 34 3 0 18 Feb 2021
Globally-Robust Neural Networks Klas Leino Zifan Wang Matt Fredrikson AAML OOD 159 131 0 16 Feb 2021
A Law of Robustness for Weight-bounded Neural Networks Hisham Husain Borja Balle 62 1 0 16 Feb 2021
Depthwise Separable Convolutions Allow for Fast and Memory-Efficient Spectral Normalization Christina Runkel Christian Etmann Michael Möller Carola-Bibiane Schönlieb 41 3 0 12 Feb 2021
Generalized Quantile Loss for Deep Neural Networks Dvir Ben-Or Michael Kolomenkin G. Shabat UQCV 31 5 0 28 Dec 2020
Bounding the Complexity of Formally Verifying Neural Networks: A Geometric Approach James Ferlez Yasser Shoukry 58 7 0 22 Dec 2020
A case for new neural network smoothness constraints Mihaela Rosca T. Weber Arthur Gretton S. Mohamed AAML 142 50 0 14 Dec 2020
Improving Adversarial Robustness via Probabilistically Compact Loss with Logit Constraints X. Li Xiangrui Li Deng Pan D. Zhu AAML 71 17 0 14 Dec 2020
Certifying Incremental Quadratic Constraints for Neural Networks via Convex Optimization Navid Hashemi Justin Ruths Mahyar Fazlyab 97 22 0 10 Dec 2020
Dissipative Deep Neural Dynamical Systems Ján Drgoňa Soumya Vasisht Aaron Tuor D. Vrabie 53 8 0 26 Nov 2020
Learning Certified Control using Contraction Metric Dawei Sun Susmit Jha Chuchu Fan 71 77 0 25 Nov 2020
Offset-free setpoint tracking using neural network controllers Patricia Pauli Johannes Köhler J. Berberich Anne Koch Frank Allgöwer 61 21 0 23 Nov 2020
Towards Robust Data-Driven Control Synthesis for Nonlinear Systems with Actuation Uncertainty Andrew J. Taylor Victor D. Dorobantu Sarah Dean Benjamin Recht Yisong Yue Aaron D. Ames 104 35 0 21 Nov 2020
Stability Analysis of Complementarity Systems with Neural Network Controllers Alp Aydinoglu Mahyar Fazlyab M. Morari Michael Posa 43 9 0 15 Nov 2020
Learning Hybrid Control Barrier Functions from Data Lars Lindemann Haimin Hu Alexander Robey Hanwen Zhang Dimos V. Dimarogonas Stephen Tu Nikolai Matni 105 51 0 08 Nov 2020
Enabling certification of verification-agnostic networks via memory-efficient semidefinite programming Sumanth Dathathri Krishnamurthy Dvijotham Alexey Kurakin Aditi Raghunathan J. Uesato ... Shreya Shankar Jacob Steinhardt Ian Goodfellow Percy Liang Pushmeet Kohli AAML 107 95 0 22 Oct 2020
Tight Second-Order Certificates for Randomized Smoothing Alexander Levine Aounon Kumar Thomas A. Goldstein Soheil Feizi AAML 55 16 0 20 Oct 2020
Planning with Learned Dynamics: Probabilistic Guarantees on Safety and Reachability via Lipschitz Constants Craig Knuth Glen Chou N. Ozay Dmitry Berenson 95 34 0 18 Oct 2020
Continuous Safety Verification of Neural Networks Chih-Hong Cheng Rongjie Yan 60 11 0 12 Oct 2020
Constraining Logits by Bounded Function for Adversarial Robustness Sekitoshi Kanai Masanori Yamada Shin'ya Yamaguchi Hiroshi Takahashi Yasutoshi Ida AAML 28 4 0 06 Oct 2020
Lipschitz Bounded Equilibrium Networks Max Revay Ruigang Wang I. Manchester 62 76 0 05 Oct 2020
Enhancing Mixup-based Semi-Supervised Learning with Explicit Lipschitz Regularization P. Gyawali S. Ghimire Linwei Wang AAML 60 7 0 23 Sep 2020
Large Norms of CNN Layers Do Not Hurt Adversarial Robustness Youwei Liang Dong Huang 48 11 0 17 Sep 2020
SoK: Certified Robustness for Deep Neural Networks Linyi Li Tao Xie Yue Liu AAML 123 131 0 09 Sep 2020
Sampling-based Reachability Analysis: A Random Set Theory Approach with Adversarial Sampling T. Lew Marco Pavone AAML 106 53 0 24 Aug 2020
Analytical bounds on the local Lipschitz constants of affine-ReLU functions Trevor Avant K. Morgansen 59 5 0 14 Aug 2020
On Mean Absolute Error for Deep Neural Network Based Vector-to-Vector Regression Jun Qi Jun Du Sabato Marco Siniscalchi Xiaoli Ma Chin-Hui Lee 62 230 0 12 Aug 2020
Convergence of Deep Fictitious Play for Stochastic Differential Games Jiequn Han Ruimeng Hu Jihao Long 83 20 0 12 Aug 2020
Improve Generalization and Robustness of Neural Networks via Weight Scale Shifting Invariant Regularizations Ziquan Liu Yufei Cui Antoni B. Chan 122 13 0 07 Aug 2020
Hierarchical Verification for Adversarial Robustness Cong Han Lim R. Urtasun Ersin Yumer AAML 36 5 0 23 Jul 2020
Adversarial Training Reduces Information and Improves Transferability M. Terzi Alessandro Achille Marco Maggipinto Gian Antonio Susto AAML 106 23 0 22 Jul 2020
Efficient Proximal Mapping of the 1-path-norm of Shallow Networks Fabian Latorre Paul Rolland Nadav Hallak Volkan Cevher AAML 65 4 0 02 Jul 2020
PEREGRiNN: Penalized-Relaxation Greedy Neural Network Verifier Haitham Khedr James Ferlez Yasser Shoukry AAML 59 5 0 18 Jun 2020
ShieldNN: A Provably Safe NN Filter for Unsafe NN Controllers James Ferlez Mahmoud M. Elnaggar Yasser Shoukry C. Fleming AAML 95 33 0 16 Jun 2020
On Lipschitz Regularization of Convolutional Layers using Toeplitz Matrix Theory Alexandre Araujo Benjamin Négrevergne Y. Chevaleyre Jamal Atif 42 0 0 15 Jun 2020
Provable tradeoffs in adversarially robust classification Yan Sun Hamed Hassani David Hong Alexander Robey 107 56 0 09 Jun 2020
The Lipschitz Constant of Self-Attention Hyunjik Kim George Papamakarios A. Mnih 92 146 0 08 Jun 2020
Lipschitz Bounds and Provably Robust Training by Laplacian Smoothing Vishaal Krishnan Abed AlRahman Al Makdah Fabio Pasqualetti OOD AAML 78 23 0 05 Jun 2020