Lipschitz regularity of deep neural networks: analysis and efficient estimation

28 May 2018

Papers citing "Lipschitz regularity of deep neural networks: analysis and efficient estimation"

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Title
Controlling the Complexity and Lipschitz Constant improves polynomial nets Zhenyu Zhu Fabian Latorre Grigorios G. Chrysos V. Cevher 24 10 0 10 Feb 2022
Width is Less Important than Depth in ReLU Neural Networks Gal Vardi Gilad Yehudai Ohad Shamir 3DV 21 9 0 08 Feb 2022
Penalizing Gradient Norm for Efficiently Improving Generalization in Deep Learning Yang Zhao Hao Zhang Xiuyuan Hu 38 116 0 08 Feb 2022
Rates of convergence for nonparametric estimation of singular distributions using generative adversarial networks Minwoo Chae GAN 32 4 0 07 Feb 2022
Decision boundaries and convex hulls in the feature space that deep learning functions learn from images Roozbeh Yousefzadeh FAtt 14 5 0 05 Feb 2022
Spelunking the Deep: Guaranteed Queries on General Neural Implicit Surfaces via Range Analysis Nicholas Sharp Alec Jacobson 42 26 0 05 Feb 2022
Certifying Out-of-Domain Generalization for Blackbox Functions Maurice Weber Linyi Li Wei Ping Zhikuan Zhao Bo-wen Li Ce Zhang OOD 29 14 0 03 Feb 2022
CNN-based regularisation for CT image reconstructions Attila Juhos MedIm 16 0 0 22 Jan 2022
Adaptive neighborhood Metric learning Kun Song Junwei Han Gong Cheng Jiwen Lu Feiping Nie 17 27 0 20 Jan 2022
Stable Long-Term Recurrent Video Super-Resolution Benjamin Naoto Chiche Arnaud Woiselle J. Frontera-Pons Jean-Luc Starck SupR 30 6 0 16 Dec 2021
On the Impact of Hard Adversarial Instances on Overfitting in Adversarial Training Chen Liu Zhichao Huang Mathieu Salzmann Tong Zhang Sabine Süsstrunk AAML 23 13 0 14 Dec 2021
ELF: Exact-Lipschitz Based Universal Density Approximator Flow Achintya Gopal 22 1 0 13 Dec 2021
Robustness Certificates for Implicit Neural Networks: A Mixed Monotone Contractive Approach Saber Jafarpour Matthew Abate A. Davydov Francesco Bullo Samuel Coogan AAML 20 8 0 10 Dec 2021
Beyond Periodicity: Towards a Unifying Framework for Activations in Coordinate-MLPs Sameera Ramasinghe Simon Lucey 22 120 0 30 Nov 2021
On the Robustness and Generalization of Deep Learning Driven Full Waveform Inversion Chengyuan Deng Youzuo Lin OOD 25 2 0 28 Nov 2021
Learning Robust Output Control Barrier Functions from Safe Expert Demonstrations Lars Lindemann Alexander Robey Lejun Jiang Satyajeet Das Stephen Tu Nikolai Matni 45 42 0 18 Nov 2021
Solving PDE-constrained Control Problems Using Operator Learning Rakhoon Hwang Jae Yong Lee J. Shin H. Hwang AI4CE 117 43 0 09 Nov 2021
Training Certifiably Robust Neural Networks with Efficient Local Lipschitz Bounds Yujia Huang Huan Zhang Yuanyuan Shi J Zico Kolter Anima Anandkumar 38 76 0 02 Nov 2021
A Dynamical System Perspective for Lipschitz Neural Networks Laurent Meunier Blaise Delattre Alexandre Araujo A. Allauzen 45 54 0 25 Oct 2021
Rethinking Neural vs. Matrix-Factorization Collaborative Filtering: the Theoretical Perspectives Zida Cheng Chuanwei Ruan Siheng Chen Sushant Kumar Ya Zhang 27 16 0 23 Oct 2021
MaGNET: Uniform Sampling from Deep Generative Network Manifolds Without Retraining Ahmed Imtiaz Humayun Randall Balestriero Richard Baraniuk OOD 43 29 0 15 Oct 2021
Towards Understanding the Data Dependency of Mixup-style Training Muthuraman Chidambaram Xiang Wang Yuzheng Hu Chenwei Wu Rong Ge UQCV 49 24 0 14 Oct 2021
Adaptive Differentially Private Empirical Risk Minimization Xiaoxia Wu Lingxiao Wang Irina Cristali Quanquan Gu Rebecca Willett 38 6 0 14 Oct 2021
Bisimulations for Neural Network Reduction P. Prabhakar 39 6 0 07 Oct 2021
Generalization Bounds For Meta-Learning: An Information-Theoretic Analysis Qi Chen Changjian Shui M. Marchand 40 43 0 29 Sep 2021
DeepPSL: End-to-end perception and reasoning Sridhar Dasaratha Sai Akhil Puranam Karmvir Singh Phogat Sunil R. Tiyyagura Nigel P. Duffy BDL ReLM LRM 42 3 0 28 Sep 2021
An automatic differentiation system for the age of differential privacy Dmitrii Usynin Alexander Ziller Moritz Knolle Andrew Trask Kritika Prakash Daniel Rueckert Georgios Kaissis 30 3 0 22 Sep 2021
Deep Spatio-temporal Sparse Decomposition for Trend Prediction and Anomaly Detection in Cardiac Electrical Conduction Xinyu Zhao Hao Yan Zhiyong Hu D. Du 31 12 0 20 Sep 2021
Gradient Normalization for Generative Adversarial Networks Yi-Lun Wu Hong-Han Shuai Zhi Rui Tam H. Chiu GAN 27 63 0 06 Sep 2021
Lipschitz Continuity Guided Knowledge Distillation Yuzhang Shang Bin Duan Ziliang Zong Liqiang Nie Yan Yan 22 29 0 29 Aug 2021
Machine Unlearning of Features and Labels Alexander Warnecke Lukas Pirch Christian Wressnegger Konrad Rieck MU 8 173 0 26 Aug 2021
Adversarial Robustness of Deep Learning: Theory, Algorithms, and Applications Wenjie Ruan Xinping Yi Xiaowei Huang AAML OOD 25 17 0 24 Aug 2021
Is Nash Equilibrium Approximator Learnable? Zhijian Duan Wenhan Huang Dinghuai Zhang Yali Du Jun Wang Yaodong Yang Xiaotie Deng 6 6 0 17 Aug 2021
Existence, Stability and Scalability of Orthogonal Convolutional Neural Networks El Mehdi Achour Franccois Malgouyres Franck Mamalet 16 20 0 12 Aug 2021
Fairness Properties of Face Recognition and Obfuscation Systems Harrison Rosenberg Brian Tang Kassem Fawaz S. Jha PICV 13 14 0 05 Aug 2021
Semi-Supervised Active Learning with Temporal Output Discrepancy Siyu Huang Tianyang Wang Haoyi Xiong Jun Huan Dejing Dou UQCV 25 66 0 29 Jul 2021
Convergence of Deep ReLU Networks Yuesheng Xu Haizhang Zhang 37 27 0 27 Jul 2021
On the expressivity of bi-Lipschitz normalizing flows Alexandre Verine Benjamin Négrevergne F. Rossi Y. Chevaleyre TPM 23 17 0 15 Jul 2021
Sensitivity analysis in differentially private machine learning using hybrid automatic differentiation Alexander Ziller Dmitrii Usynin Moritz Knolle Kritika Prakash Andrew Trask R. Braren Marcus R. Makowski Daniel Rueckert Georgios Kaissis 20 5 0 09 Jul 2021
Provable Lipschitz Certification for Generative Models Matt Jordan A. Dimakis 22 14 0 06 Jul 2021
Local-Global Knowledge Distillation in Heterogeneous Federated Learning with Non-IID Data Dezhong Yao Wanning Pan Yutong Dai Yao Wan Xiaofeng Ding Hai Jin Zheng Xu Lichao Sun FedML 28 50 0 30 Jun 2021
On Incorporating Inductive Biases into VAEs Ning Miao Emile Mathieu N. Siddharth Yee Whye Teh Tom Rainforth CML DRL 30 10 0 25 Jun 2021
Boosting Offline Reinforcement Learning with Residual Generative Modeling Hua Wei Deheng Ye Zhao Liu Hao Wu Bo Yuan Qiang Fu Wei Yang Z. Li OffRL 26 9 0 19 Jun 2021
Proximal Optimal Transport Modeling of Population Dynamics Charlotte Bunne Laetitia Meng-Papaxanthos Andreas Krause Marco Cuturi OT 51 82 0 11 Jun 2021
Is Homophily a Necessity for Graph Neural Networks? Yao Ma Xiaorui Liu Neil Shah Jiliang Tang 30 228 0 11 Jun 2021
What training reveals about neural network complexity Andreas Loukas Marinos Poiitis Stefanie Jegelka 28 11 0 08 Jun 2021
Learning by Transference: Training Graph Neural Networks on Growing Graphs J. Cerviño Luana Ruiz Alejandro Ribeiro GNN 28 18 0 07 Jun 2021
Measuring Generalization with Optimal Transport Ching-Yao Chuang Youssef Mroueh Kristjan Greenewald Antonio Torralba Stefanie Jegelka OT 46 25 0 07 Jun 2021
Representation Learning Beyond Linear Prediction Functions Ziping Xu Ambuj Tewari 11 21 0 31 May 2021
LipBaB: Computing exact Lipschitz constant of ReLU networks Aritra Bhowmick Meenakshi D'Souza G. S. Raghavan 13 16 0 12 May 2021