Residual Flows for Invertible Generative Modeling

6 June 2019

Papers citing "Residual Flows for Invertible Generative Modeling"

41 / 41 papers shown

Title
WaterFlow: Learning Fast & Robust Watermarks using Stable Diffusion Vinay Shukla Prachee Sharma Ryan Rossi Sungchul Kim Tong Yu Aditya Grover WIGM 106 0 0 15 Apr 2025
Model Synthesis for Zero-Shot Model Attribution Tianyun Yang Juan Cao Danding Wang Chang Xu WIGM 93 4 0 20 Jan 2025
Generative Modelling with High-Order Langevin Dynamics Ziqiang Shi Rujie Liu DiffM 74 2 0 03 Jan 2025
vMF-Contact: Uncertainty-aware Evidential Learning for Probabilistic Contact-grasp in Noisy Clutter Yitian Shi Edgar Welte Maximilian Gilles Rania Rayyes 61 3 0 06 Nov 2024
Importance Corrected Neural JKO Sampling Johannes Hertrich Robert Gruhlke 61 2 0 29 Jul 2024
Variational Bayesian Optimal Experimental Design with Normalizing Flows Jiayuan Dong Christian L. Jacobsen Mehdi Khalloufi Maryam Akram Wanjiao Liu Karthik Duraisamy Xun Huan BDL 83 7 0 08 Apr 2024
Diffusion Models with Deterministic Normalizing Flow Priors Mohsen Zand Ali Etemad Michael A. Greenspan DiffM 61 2 0 03 Sep 2023
Computing excited states of molecules using normalizing flows Yahya Saleh Álvaro Fernández Corral Emil Vogt Armin Iske J. Küpper A. Yachmenev 49 7 0 31 Aug 2023
Complementary Frequency-Varying Awareness Network for Open-Set Fine-Grained Image Recognition Qiulei Dong Hong Wang Qiulei Dong 49 0 0 14 Jul 2023
Principled Interpolation in Normalizing Flows Samuel G. Fadel Sebastian Mair Ricardo da S. Torres Ulf Brefeld 102 3 0 22 Oct 2020
Large-time asymptotics in deep learning Carlos Esteve Borjan Geshkovski Dario Pighin Enrique Zuazua 54 34 0 06 Aug 2020
Efficient Optimization of Loops and Limits with Randomized Telescoping Sums Alex Beatson Ryan P. Adams 46 21 0 16 May 2019
Hybrid Models with Deep and Invertible Features Eric T. Nalisnick Akihiro Matsukawa Yee Whye Teh Dilan Görür Balaji Lakshminarayanan BDL DRL 55 99 0 07 Feb 2019
Flow++: Improving Flow-Based Generative Models with Variational Dequantization and Architecture Design Jonathan Ho Xi Chen A. Srinivas Yan Duan Pieter Abbeel DRL 38 446 0 01 Feb 2019
Invertible Residual Networks Jens Behrmann Will Grathwohl Ricky T. Q. Chen David Duvenaud J. Jacobsen UQCV TPM 71 621 0 02 Nov 2018
Excessive Invariance Causes Adversarial Vulnerability J. Jacobsen Jens Behrmann R. Zemel Matthias Bethge AAML 45 166 0 01 Nov 2018
Three Mechanisms of Weight Decay Regularization Guodong Zhang Chaoqi Wang Bowen Xu Roger C. Grosse 42 257 0 29 Oct 2018
FFJORD: Free-form Continuous Dynamics for Scalable Reversible Generative Models Will Grathwohl Ricky T. Q. Chen J. Bettencourt Ilya Sutskever David Duvenaud DRL 46 861 0 02 Oct 2018
Glow: Generative Flow with Invertible 1x1 Convolutions Diederik P. Kingma Prafulla Dhariwal BDL DRL 194 3,110 0 09 Jul 2018
Neural Ordinary Differential Equations T. Chen Yulia Rubanova J. Bettencourt David Duvenaud AI4CE 201 5,024 0 19 Jun 2018
Autoregressive Quantile Networks for Generative Modeling Georg Ostrovski Will Dabney Rémi Munos DRL 49 87 0 14 Jun 2018
Backpropagation for Implicit Spectral Densities Aditya A. Ramesh Yann LeCun 35 10 0 01 Jun 2018
Regularisation of Neural Networks by Enforcing Lipschitz Continuity Henry Gouk E. Frank Bernhard Pfahringer M. Cree 91 473 0 12 Apr 2018
Reviving and Improving Recurrent Back-Propagation Renjie Liao Yuwen Xiong Ethan Fetaya Lisa Zhang Kijung Yoon Xaq Pitkow R. Urtasun R. Zemel BDL 57 118 0 16 Mar 2018
Stochastic Chebyshev Gradient Descent for Spectral Optimization Insu Han H. Avron Jinwoo Shin 26 11 0 18 Feb 2018
Spectral Normalization for Generative Adversarial Networks Takeru Miyato Toshiki Kataoka Masanori Koyama Yuichi Yoshida ODL 127 4,421 0 16 Feb 2018
Estimating the Spectral Density of Large Implicit Matrices Ryan P. Adams Jeffrey Pennington Matthew J. Johnson Jamie Smith Yaniv Ovadia Brian Patton J. Saunderson 39 33 0 09 Feb 2018
Searching for Activation Functions Prajit Ramachandran Barret Zoph Quoc V. Le 44 602 0 16 Oct 2017
Reversible Architectures for Arbitrarily Deep Residual Neural Networks B. Chang Lili Meng E. Haber Lars Ruthotto David Begert E. Holtham AI4CE 57 262 0 12 Sep 2017
The Reversible Residual Network: Backpropagation Without Storing Activations Aidan Gomez Mengye Ren R. Urtasun Roger C. Grosse 50 545 0 14 Jul 2017
Unbiasing Truncated Backpropagation Through Time Corentin Tallec Yann Ollivier 46 75 0 23 May 2017
Improving Variational Inference with Inverse Autoregressive Flow Diederik P. Kingma Tim Salimans Rafal Jozefowicz Xi Chen Ilya Sutskever Max Welling BDL DRL 76 1,805 0 15 Jun 2016
Faster Eigenvector Computation via Shift-and-Invert Preconditioning Dan Garber Laurent Dinh Chi Jin Jascha Narain Sohl-Dickstein Samy Bengio Praneeth Netrapalli Aaron Sidford 168 3,670 0 26 May 2016
Pixel Recurrent Neural Networks Aaron van den Oord Nal Kalchbrenner Koray Kavukcuoglu SSeg GAN 377 2,563 0 25 Jan 2016
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 1.2K 192,638 0 10 Dec 2015
A note on the evaluation of generative models Lucas Theis Aaron van den Oord Matthias Bethge EGVM 61 1,139 0 05 Nov 2015
Variational Inference with Normalizing Flows Danilo Jimenez Rezende S. Mohamed DRL BDL 238 4,143 0 21 May 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 632 149,474 0 22 Dec 2014
NICE: Non-linear Independent Components Estimation Laurent Dinh David M. Krueger Yoshua Bengio DRL BDL 79 2,246 0 30 Oct 2014
Auto-Encoding Variational Bayes Diederik P. Kingma Max Welling BDL 336 16,972 0 20 Dec 2013
A general method for debiasing a Monte Carlo estimator D. McLeish 87 115 0 12 May 2010