Invertible Residual Networks

2 November 2018

Papers citing "Invertible Residual Networks"

50 / 153 papers shown

Title
EBMs Trained with Maximum Likelihood are Generator Models Trained with a Self-adverserial Loss Zhisheng Xiao Qing Yan Y. Amit 32 2 0 23 Feb 2021
Momentum Residual Neural Networks Michael E. Sander Pierre Ablin Mathieu Blondel Gabriel Peyré 27 57 0 15 Feb 2021
Jacobian Determinant of Normalizing Flows Huadong Liao Jiawei He DRL 19 7 0 12 Feb 2021
MALI: A memory efficient and reverse accurate integrator for Neural ODEs Juntang Zhuang Nicha Dvornek S. Tatikonda James S. Duncan 27 49 0 09 Feb 2021
Exploring Adversarial Examples via Invertible Neural Networks Ruqi Bai S. Bagchi David I. Inouye AAML 27 2 0 24 Dec 2020
A case for new neural network smoothness constraints Mihaela Rosca T. Weber Arthur Gretton S. Mohamed AAML 35 48 0 14 Dec 2020
Convex Potential Flows: Universal Probability Distributions with Optimal Transport and Convex Optimization Chin-Wei Huang Ricky T. Q. Chen Christos Tsirigotis Aaron Courville OT 119 95 0 10 Dec 2020
Feature Space Singularity for Out-of-Distribution Detection Haiwen Huang Zhihan Li Lulu Wang Sishuo Chen Bin Dong Xinyu Zhou OODD 22 65 0 30 Nov 2020
Score-Based Generative Modeling through Stochastic Differential Equations Yang Song Jascha Narain Sohl-Dickstein Diederik P. Kingma Abhishek Kumar Stefano Ermon Ben Poole DiffM SyDa 81 6,113 0 26 Nov 2020
Self Normalizing Flows Thomas Anderson Keller Jorn W. T. Peters P. Jaini Emiel Hoogeboom Patrick Forré Max Welling 30 14 0 14 Nov 2020
On Attribution of Deepfakes Baiwu Zhang Jin Peng Zhou Ilia Shumailov Nicolas Papernot WIGM 32 11 0 20 Aug 2020
Adversarial Training Reduces Information and Improves Transferability M. Terzi Alessandro Achille Marco Maggipinto Gian Antonio Susto AAML 24 23 0 22 Jul 2020
Discrete Point Flow Networks for Efficient Point Cloud Generation Roman Klokov Edmond Boyer Jakob Verbeek 3DPC 26 107 0 20 Jul 2020
A Systematic Survey on Deep Generative Models for Graph Generation Xiaojie Guo Liang Zhao MedIm 46 147 0 13 Jul 2020
Relative gradient optimization of the Jacobian term in unsupervised deep learning Luigi Gresele G. Fissore Adrián Javaloy Bernhard Schölkopf Aapo Hyvarinen DRL 19 22 0 26 Jun 2020
SRFlow: Learning the Super-Resolution Space with Normalizing Flow Andreas Lugmayr Martin Danelljan Luc Van Gool Radu Timofte SupR DRL 23 356 0 25 Jun 2020
Simple and Principled Uncertainty Estimation with Deterministic Deep Learning via Distance Awareness Jeremiah Zhe Liu Zi Lin Shreyas Padhy Dustin Tran Tania Bedrax-Weiss Balaji Lakshminarayanan UQCV BDL 37 437 0 17 Jun 2020
Understanding and Mitigating Exploding Inverses in Invertible Neural Networks Jens Behrmann Paul Vicol Kuan-Chieh Jackson Wang Roger C. Grosse J. Jacobsen 23 93 0 16 Jun 2020
The Lipschitz Constant of Self-Attention Hyunjik Kim George Papamakarios A. Mnih 14 135 0 08 Jun 2020
The Convolution Exponential and Generalized Sylvester Flows Emiel Hoogeboom Victor Garcia Satorras Jakub M. Tomczak Max Welling 27 28 0 02 Jun 2020
Invertible Image Rescaling Mingqing Xiao Shuxin Zheng Chang-Shu Liu Yaolong Wang Di He Guolin Ke Jiang Bian Zhouchen Lin Tie-Yan Liu SupR 33 234 0 12 May 2020
Parameterizing uncertainty by deep invertible networks, an application to reservoir characterization G. Rizzuti Ali Siahkoohi Philipp A. Witte Felix J. Herrmann UQCV 33 20 0 16 Apr 2020
Hybrid Models for Open Set Recognition Hongjie Zhang Ang Li Jie Guo Yanwen Guo BDL 28 184 0 27 Mar 2020
On Feature Normalization and Data Augmentation Boyi Li Felix Wu Ser-Nam Lim Serge J. Belongie Kilian Q. Weinberger 21 134 0 25 Feb 2020
Stochastic Latent Residual Video Prediction Jean-Yves Franceschi E. Delasalles Mickaël Chen Sylvain Lamprier Patrick Gallinari VGen 28 159 0 21 Feb 2020
Deep Gaussian Markov Random Fields Per Sidén Fredrik Lindsten BDL 28 22 0 18 Feb 2020
Augmented Normalizing Flows: Bridging the Gap Between Generative Flows and Latent Variable Models Chin-Wei Huang Laurent Dinh Aaron Courville DRL 31 87 0 17 Feb 2020
Stochastic Normalizing Flows Hao Wu Jonas Köhler Frank Noé 57 176 0 16 Feb 2020
Latent Normalizing Flows for Many-to-Many Cross-Domain Mappings Shweta Mahajan Iryna Gurevych Stefan Roth DRL 21 36 0 16 Feb 2020
How to train your neural ODE: the world of Jacobian and kinetic regularization Chris Finlay J. Jacobsen L. Nurbekyan Adam M. Oberman 11 296 0 07 Feb 2020
SympNets: Intrinsic structure-preserving symplectic networks for identifying Hamiltonian systems Pengzhan Jin Zhen Zhang Aiqing Zhu Yifa Tang George Karniadakis 21 21 0 11 Jan 2020
Semi-Supervised Learning with Normalizing Flows Pavel Izmailov Polina Kirichenko Marc Finzi A. Wilson DRL BDL 40 111 0 30 Dec 2019
Getting Topology and Point Cloud Generation to Mesh Austin Dill Chun-Liang Li Songwei Ge Eunsu Kang 3DPC 25 3 0 08 Dec 2019
Your Classifier is Secretly an Energy Based Model and You Should Treat it Like One Will Grathwohl Kuan-Chieh Jackson Wang J. Jacobsen David Duvenaud Mohammad Norouzi Kevin Swersky VLM 43 528 0 06 Dec 2019
Normalizing Flows for Probabilistic Modeling and Inference George Papamakarios Eric T. Nalisnick Danilo Jimenez Rezende S. Mohamed Balaji Lakshminarayanan TPM AI4CE 59 1,631 0 05 Dec 2019
Learning Multi-layer Latent Variable Model via Variational Optimization of Short Run MCMC for Approximate Inference Erik Nijkamp Bo Pang Tian Han Linqi Zhou Song-Chun Zhu Ying Nian Wu BDL DRL 19 2 0 04 Dec 2019
FIS-GAN: GAN with Flow-based Importance Sampling Shiyu Yi Donglin Zhan Wenqing Zhang Zhengyang Geng Kang An Hao Wang GAN 24 3 0 06 Oct 2019
Relaxing Bijectivity Constraints with Continuously Indexed Normalising Flows R. Cornish Anthony L. Caterini George Deligiannidis Arnaud Doucet 22 2 0 30 Sep 2019
GResNet: Graph Residual Network for Reviving Deep GNNs from Suspended Animation Jiawei Zhang Lin Meng 21 52 0 12 Sep 2019
Conditional Flow Variational Autoencoders for Structured Sequence Prediction Apratim Bhattacharyya M. Hanselmann Mario Fritz Bernt Schiele C. Straehle BDL DRL AI4TS 27 84 0 24 Aug 2019
Stochastic Neural Network with Kronecker Flow Chin-Wei Huang Ahmed Touati Pascal Vincent Gintare Karolina Dziugaite Alexandre Lacoste Aaron Courville BDL 27 8 0 10 Jun 2019
Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift Yaniv Ovadia Emily Fertig Jie Jessie Ren Zachary Nado D. Sculley Sebastian Nowozin Joshua V. Dillon Balaji Lakshminarayanan Jasper Snoek UQCV 29 1,658 0 06 Jun 2019
Adversarial Robustness as a Prior for Learned Representations Logan Engstrom Andrew Ilyas Shibani Santurkar Dimitris Tsipras Brandon Tran A. Madry OOD AAML 27 63 0 03 Jun 2019
HINT: Hierarchical Invertible Neural Transport for Density Estimation and Bayesian Inference Jakob Kruse Gianluca Detommaso Ullrich Kothe Robert Scheichl 13 45 0 25 May 2019
Fast Flow Reconstruction via Robust Invertible nxn Convolution Thanh-Dat Truong Khoa Luu C. Duong Ngan Le M. Tran 19 7 0 24 May 2019
Learning Non-Convergent Non-Persistent Short-Run MCMC Toward Energy-Based Model Erik Nijkamp Mitch Hill Song-Chun Zhu Ying Nian Wu 29 209 0 22 Apr 2019
Exploiting Excessive Invariance caused by Norm-Bounded Adversarial Robustness J. Jacobsen Jens Behrmann Nicholas Carlini Florian Tramèr Nicolas Papernot AAML 24 46 0 25 Mar 2019
Revisiting Self-Supervised Visual Representation Learning Alexander Kolesnikov Xiaohua Zhai Lucas Beyer SSL 53 715 0 25 Jan 2019
A Style-Based Generator Architecture for Generative Adversarial Networks Tero Karras S. Laine Timo Aila 306 10,378 0 12 Dec 2018
Spread Divergence Mingtian Zhang Peter Hayes Thomas Bird Raza Habib David Barber MedIm UD 30 20 0 21 Nov 2018