Understanding and Mitigating Exploding Inverses in Invertible Neural Networks

16 June 2020

Jens Behrmann

Paul Vicol

Kuan-Chieh Jackson Wang

Roger C. Grosse

J. Jacobsen

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Papers citing "Understanding and Mitigating Exploding Inverses in Invertible Neural Networks"

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Title
Constructing Fair Latent Space for Intersection of Fairness and Explainability Hyungjun Joo Hyeonggeun Han Sehwan Kim Sangwoo Hong Jungwoo Lee 40 0 0 23 Dec 2024
Generative Topological Networks Alona Levy-Jurgenson Z. Yakhini 38 0 0 21 Jun 2024
Boosting Flow-based Generative Super-Resolution Models via Learned Prior Li-Yuan Tsao Yi-Chen Lo Chia-Che Chang Hao-Wei Chen Roy Tseng Chien Feng Chun-Yi Lee SupR 19 4 0 16 Mar 2024
Stable Training of Normalizing Flows for High-dimensional Variational Inference Daniel Andrade BDL TPM 43 1 0 26 Feb 2024
Monotone, Bi-Lipschitz, and Polyak-Lojasiewicz Networks Ruigang Wang Krishnamurthy Dvijotham I. Manchester 19 5 0 02 Feb 2024
Learning from small data sets: Patch-based regularizers in inverse problems for image reconstruction Moritz Piening Fabian Altekrüger J. Hertrich Paul Hagemann Andrea Walther Gabriele Steidl 24 6 0 27 Dec 2023
Conditional Generative Models are Provably Robust: Pointwise Guarantees for Bayesian Inverse Problems Fabian Altekrüger Paul Hagemann Gabriele Steidl TPM 21 9 0 28 Mar 2023
A Lifted Bregman Formulation for the Inversion of Deep Neural Networks Xiaoyu Wang Martin Benning 28 2 0 01 Mar 2023
Certified Invertibility in Neural Networks via Mixed-Integer Programming Tianqi Cui Tom S. Bertalan George J. Pappas M. Morari Ioannis G. Kevrekidis Mahyar Fazlyab AAML 19 2 0 27 Jan 2023
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
Normalizing Flow-based Day-Ahead Wind Power Scenario Generation for Profitable and Reliable Delivery Commitments by Wind Farm Operators Eike Cramer Leonard Paeleke Alexander Mitsos Manuel Dahmen 13 11 0 05 Apr 2022
Artefact Retrieval: Overview of NLP Models with Knowledge Base Access Vilém Zouhar Marius Mosbach Debanjali Biswas Dietrich Klakow KELM 19 4 0 24 Jan 2022
Generalized Normalizing Flows via Markov Chains Paul Hagemann J. Hertrich Gabriele Steidl BDL DiffM AI4CE 22 22 0 24 Nov 2021
Resampling Base Distributions of Normalizing Flows Vincent Stimper Bernhard Schölkopf José Miguel Hernández-Lobato BDL 22 32 0 29 Oct 2021
Insights from Generative Modeling for Neural Video Compression Ruihan Yang Yibo Yang Joseph Marino Stephan Mandt VGen 27 15 0 28 Jul 2021
Copula-Based Normalizing Flows M. Laszkiewicz Johannes Lederer Asja Fischer 27 7 0 15 Jul 2021
Principal Component Density Estimation for Scenario Generation Using Normalizing Flows Eike Cramer Alexander Mitsos Raúl Tempone Manuel Dahmen 27 13 0 21 Apr 2021
iVPF: Numerical Invertible Volume Preserving Flow for Efficient Lossless Compression Shifeng Zhang Chen Zhang Ning Kang Zhenguo Li 25 37 0 30 Mar 2021
Flow-based Self-supervised Density Estimation for Anomalous Sound Detection Kota Dohi Takashi Endo Harsh Purohit Ryo Tanabe Y. Kawaguchi 22 58 0 16 Mar 2021
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
Regularization with Latent Space Virtual Adversarial Training Genki Osada Budrul Ahsan Revoti Prasad Bora Takashi Nishide 22 14 0 26 Nov 2020
IDF++: Analyzing and Improving Integer Discrete Flows for Lossless Compression Rianne van den Berg A. Gritsenko Mostafa Dehghani C. Sønderby Tim Salimans 19 59 0 22 Jun 2020
Stable Neural Flows Stefano Massaroli Michael Poli Michelangelo Bin Jinkyoo Park Atsushi Yamashita Hajime Asama 40 30 0 18 Mar 2020