Invertible Residual Networks

2 November 2018

Papers citing "Invertible Residual Networks"

50 / 120 papers shown

Title
Flowification: Everything is a Normalizing Flow Bálint Máté Samuel Klein T. Golling Franccois Fleuret 18 3 0 30 May 2022
A Simple Approach to Improve Single-Model Deep Uncertainty via Distance-Awareness J. Liu Shreyas Padhy Jie Jessie Ren Zi Lin Yeming Wen Ghassen Jerfel Zachary Nado Jasper Snoek Dustin Tran Balaji Lakshminarayanan UQCV BDL 16 48 0 01 May 2022
SIReN-VAE: Leveraging Flows and Amortized Inference for Bayesian Networks Jacobie Mouton Steve Kroon DRL BDL 20 0 0 23 Apr 2022
CaDeX: Learning Canonical Deformation Coordinate Space for Dynamic Surface Representation via Neural Homeomorphism Jiahui Lei Kostas Daniilidis 26 53 0 30 Mar 2022
Deep Koopman Operator with Control for Nonlinear Systems Hao-bin Shi M. Meng 6 74 0 16 Feb 2022
Global Optimization Networks Sen Zhao Erez Louidor Ilan Oleksandr Mangylov Maya R. Gupta 18 5 0 02 Feb 2022
FedComm: Federated Learning as a Medium for Covert Communication Dorjan Hitaj Giulio Pagnotta B. Hitaj F. Pérez-Cruz L. Mancini FedML 25 10 0 21 Jan 2022
A Compact Neural Network-based Algorithm for Robust Image Watermarking Hongcai Xu Rong Wang Jia Wei Shao-Ping Lu 22 13 0 27 Dec 2021
Interpolated Joint Space Adversarial Training for Robust and Generalizable Defenses Chun Pong Lau Jiang-Long Liu Hossein Souri Wei-An Lin S. Feizi Ramalingam Chellappa AAML 27 12 0 12 Dec 2021
Decomposing Representations for Deterministic Uncertainty Estimation Haiwen Huang Joost R. van Amersfoort Y. Gal UQCV OOD UD 16 1 0 01 Dec 2021
Forward Operator Estimation in Generative Models with Kernel Transfer Operators Z. Huang Rudrasis Chakraborty Vikas Singh GAN 14 3 0 01 Dec 2021
Characteristic Neural Ordinary Differential Equations Xingzi Xu Ali Hasan Khalil Elkhalil Jie Ding Vahid Tarokh BDL 19 3 0 25 Nov 2021
Generalized Normalizing Flows via Markov Chains Paul Hagemann J. Hertrich Gabriele Steidl BDL DiffM AI4CE 22 22 0 24 Nov 2021
On Training Implicit Models Zhengyang Geng Xinyu Zhang Shaojie Bai Yisen Wang Zhouchen Lin 59 69 0 09 Nov 2021
Constructing Neural Network-Based Models for Simulating Dynamical Systems Christian Møldrup Legaard Thomas Schranz G. Schweiger Ján Drgovna Basak Falay C. Gomes Alexandros Iosifidis M. Abkar P. Larsen PINN AI4CE 20 93 0 02 Nov 2021
Resampling Base Distributions of Normalizing Flows Vincent Stimper Bernhard Schölkopf José Miguel Hernández-Lobato BDL 22 32 0 29 Oct 2021
Sinkformers: Transformers with Doubly Stochastic Attention Michael E. Sander Pierre Ablin Mathieu Blondel Gabriel Peyré 21 76 0 22 Oct 2021
PixelPyramids: Exact Inference Models from Lossless Image Pyramids Shweta Mahajan Stefan Roth TPM 10 2 0 17 Oct 2021
Deep Classifiers with Label Noise Modeling and Distance Awareness Vincent Fortuin Mark Collier F. Wenzel J. Allingham J. Liu Dustin Tran Balaji Lakshminarayanan Jesse Berent Rodolphe Jenatton E. Kokiopoulou UQCV 26 11 0 06 Oct 2021
Manifold-preserved GANs Haozhe Liu Hanbang Liang Xianxu Hou Haoqian Wu Feng Liu Linlin Shen 41 5 0 18 Sep 2021
Deep Generative Modeling for Protein Design Alexey Strokach Philip M. Kim AI4CE 179 90 0 31 Aug 2021
m-RevNet: Deep Reversible Neural Networks with Momentum Duo Li Shangqi Gao 8 5 0 12 Aug 2021
Boundary of Distribution Support Generator (BDSG): Sample Generation on the Boundary Nikolaos Dionelis Mehrdad Yaghoobi Sotirios A. Tsaftaris 8 12 0 21 Jul 2021
Featurized Density Ratio Estimation Kristy Choi Madeline Liao Stefano Ermon TPM 14 22 0 05 Jul 2021
Task-agnostic Continual Learning with Hybrid Probabilistic Models Polina Kirichenko Mehrdad Farajtabar Dushyant Rao Balaji Lakshminarayanan Nir Levine Ang Li Huiyi Hu A. Wilson Razvan Pascanu VLM BDL CLL 14 19 0 24 Jun 2021
Memory-Efficient Differentiable Transformer Architecture Search Yuekai Zhao Li Dong Yelong Shen Zhihua Zhang Furu Wei Weizhu Chen ViT 22 17 0 31 May 2021
Efficient and Accurate Gradients for Neural SDEs Patrick Kidger James Foster Xuechen Li Terry Lyons DiffM 19 60 0 27 May 2021
PointLIE: Locally Invertible Embedding for Point Cloud Sampling and Recovery Weibing Zhao Xu Yan Jiantao Gao Ruimao Zhang Jiayan Zhang Zhen Li Song Wu Shuguang Cui 3DPC 9 7 0 30 Apr 2021
Invertible Denoising Network: A Light Solution for Real Noise Removal Yang Liu Zhenyue Qin Saeed Anwar Pan Ji Dongwoo Kim Sabrina Caldwell Tom Gedeon 70 143 0 21 Apr 2021
Deep Generative Modelling: A Comparative Review of VAEs, GANs, Normalizing Flows, Energy-Based and Autoregressive Models Sam Bond-Taylor Adam Leach Yang Long Chris G. Willcocks VLM TPM 36 478 0 08 Mar 2021
Momentum Residual Neural Networks Michael E. Sander Pierre Ablin Mathieu Blondel Gabriel Peyré 19 56 0 15 Feb 2021
Jacobian Determinant of Normalizing Flows Huadong Liao Jiawei He DRL 11 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 22 49 0 09 Feb 2021
A case for new neural network smoothness constraints Mihaela Rosca T. Weber A. Gretton S. Mohamed AAML 17 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 112 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 20 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 8 6,045 0 26 Nov 2020
Self Normalizing Flows Thomas Anderson Keller Jorn W. T. Peters P. Jaini Emiel Hoogeboom Patrick Forré Max Welling 22 14 0 14 Nov 2020
On Attribution of Deepfakes Baiwu Zhang Jin Peng Zhou Ilia Shumailov Nicolas Papernot WIGM 24 11 0 20 Aug 2020
Adversarial Training Reduces Information and Improves Transferability M. Terzi Alessandro Achille Marco Maggipinto Gian Antonio Susto AAML 6 23 0 22 Jul 2020
A Systematic Survey on Deep Generative Models for Graph Generation Xiaojie Guo Liang Zhao MedIm 35 146 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 6 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 8 356 0 25 Jun 2020
Understanding and Mitigating Exploding Inverses in Invertible Neural Networks Jens Behrmann Paul Vicol Kuan-Chieh Jackson Wang Roger C. Grosse J. Jacobsen 8 92 0 16 Jun 2020
The Lipschitz Constant of Self-Attention Hyunjik Kim George Papamakarios A. Mnih 8 134 0 08 Jun 2020
The Convolution Exponential and Generalized Sylvester Flows Emiel Hoogeboom Victor Garcia Satorras Jakub M. Tomczak Max Welling 17 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 17 234 0 12 May 2020
On Feature Normalization and Data Augmentation Boyi Li Felix Wu Ser-Nam Lim Serge J. Belongie Kilian Q. Weinberger 13 134 0 25 Feb 2020
Stochastic Latent Residual Video Prediction Jean-Yves Franceschi E. Delasalles Mickaël Chen Sylvain Lamprier Patrick Gallinari VGen 26 159 0 21 Feb 2020
Augmented Normalizing Flows: Bridging the Gap Between Generative Flows and Latent Variable Models Chin-Wei Huang Laurent Dinh Aaron Courville DRL 24 87 0 17 Feb 2020