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Coupling-based Invertible Neural Networks Are Universal Diffeomorphism Approximators

20 June 2020

Papers citing "Coupling-based Invertible Neural Networks Are Universal Diffeomorphism Approximators"

50 / 76 papers shown

Title
FORT: Forward-Only Regression Training of Normalizing Flows Danyal Rehman Oscar Davis Jiarui Lu Jian Tang M. Bronstein Yoshua Bengio Alexander Tong A. Bose OOD 40 0 0 01 Jun 2025
Design of Restricted Normalizing Flow towards Arbitrary Stochastic Policy with Computational Efficiency Taisuke Kobayashi Takumi Aotani 176 5 0 17 Dec 2024
Can neural operators always be continuously discretized? Takashi Furuya Michael Puthawala Maarten V. de Hoop Matti Lassas 113 1 0 04 Dec 2024
Deep Koopman-layered Model with Universal Property Based on Toeplitz Matrices Yuka Hashimoto Tomoharu Iwata 87 0 0 03 Oct 2024
Deep Learning in Medical Image Registration: Magic or Mirage? Rohit Jena Deeksha Sethi Pratik Chaudhari James C. Gee OOD 82 10 0 11 Aug 2024
Flexible Tails for Normalizing Flows Tennessee Hickling Dennis Prangle 64 0 0 22 Jun 2024
VeriFlow: Modeling Distributions for Neural Network Verification Faried Abu Zaid Daniel Neider Mustafa Yalçıner 135 0 0 20 Jun 2024
Weak Generative Sampler to Efficiently Sample Invariant Distribution of Stochastic Differential Equation Zhiqiang Cai Yu Cao Yuanfei Huang Xiang Zhou DiffM 96 0 0 29 May 2024
Transport of Algebraic Structure to Latent Embeddings Samuel Pfrommer Brendon G. Anderson Somayeh Sojoudi 68 0 0 27 May 2024
Enhancing Accuracy in Generative Models via Knowledge Transfer Xinyu Tian Xiaotong Shen 84 2 0 27 May 2024
ASPIRE: Iterative Amortized Posterior Inference for Bayesian Inverse Problems Rafael Orozco Ali Siahkoohi M. Louboutin Felix J. Herrmann 77 2 0 08 May 2024
Learning Neural Contracting Dynamics: Extended Linearization and Global Guarantees Sean Jaffe A. Davydov Deniz Lapsekili Ambuj K. Singh Francesco Bullo 72 2 0 12 Feb 2024
Dimension Mixer: A Generalized Method for Structured Sparsity in Deep Neural Networks Suman Sapkota Binod Bhattarai 88 0 0 30 Nov 2023
Free-form Flows: Make Any Architecture a Normalizing Flow Felix Dräxler Peter Sorrenson Lea Zimmermann Armand Rousselot Ullrich Kothe TPM DRL AI4CE BDL 103 11 0 25 Oct 2023
On the Stability of Iterative Retraining of Generative Models on their own Data Quentin Bertrand A. Bose Alexandre Duplessis Marco Jiralerspong Gauthier Gidel 164 51 0 30 Sep 2023
Learning Orbitally Stable Systems for Diagrammatically Teaching Weiming Zhi Tianyi Zhang Matthew Johnson-Roberson 69 3 0 19 Sep 2023
Finding emergence in data by maximizing effective information Mingzhe Yang Zhipeng Wang Kaiwei Liu Ying Rong Bing Yuan Jiang Zhang CML 51 6 0 19 Aug 2023
On the Approximation of Bi-Lipschitz Maps by Invertible Neural Networks Bangti Jin Zehui Zhou Jun Zou 88 3 0 18 Aug 2023
Sig-Splines: universal approximation and convex calibration of time series generative models Magnus Wiese Phillip Murray R. Korn AI4TS 151 1 0 19 Jul 2023
On the Convergence Rate of Gaussianization with Random Rotations Felix Dräxler Lars Kühmichel Armand Rousselot Jens Müller Christoph Schnörr Ullrich Kothe 85 3 0 23 Jun 2023
Globally injective and bijective neural operators Takashi Furuya Michael Puthawala Matti Lassas Maarten V. de Hoop 92 11 0 06 Jun 2023
Learning Linear Causal Representations from Interventions under General Nonlinear Mixing Simon Buchholz Goutham Rajendran Elan Rosenfeld Bryon Aragam Bernhard Schölkopf Pradeep Ravikumar CML 110 65 0 04 Jun 2023
Minimum Width of Leaky-ReLU Neural Networks for Uniform Universal Approximation Liang Li Yifei Duan Guanghua Ji Yongqiang Cai MLT 96 14 0 29 May 2023
Bounded KRnet and its applications to density estimation and approximation Lisheng Zeng Xiaoliang Wan Tao Zhou 66 5 0 15 May 2023
A Flow-Based Generative Model for Rare-Event Simulation Lachlan J. Gibson Marcus Hoerger Dirk P. Kroese 50 4 0 13 May 2023
Conditional Generative Models are Provably Robust: Pointwise Guarantees for Bayesian Inverse Problems Fabian Altekrüger Paul Hagemann Gabriele Steidl TPM 64 9 0 28 Mar 2023
LU-Net: Invertible Neural Networks Based on Matrix Factorization Robin Shing Moon Chan Sarina Penquitt Hanno Gottschalk BDL 67 4 0 21 Feb 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 63 2 0 27 Jan 2023
Whitening Convergence Rate of Coupling-based Normalizing Flows Felix Dräxler Christoph Schnörr Ullrich Kothe 120 7 0 25 Oct 2022
Transfer learning with affine model transformation Shunya Minami Kenji Fukumizu Yoshihiro Hayashi Ryo Yoshida 69 1 0 18 Oct 2022
Invertible Monotone Operators for Normalizing Flows Byeongkeun Ahn Chiyoon Kim Youngjoon Hong Hyunwoo J. Kim TPM 105 8 0 15 Oct 2022
Approximation of nearly-periodic symplectic maps via structure-preserving neural networks Valentin Duruisseaux J. Burby Q. Tang 99 11 0 11 Oct 2022
Invertible Rescaling Network and Its Extensions Mingqing Xiao Shuxin Zheng Chang-Shu Liu Zhouchen Lin Tie-Yan Liu 71 28 0 09 Oct 2022
Vanilla Feedforward Neural Networks as a Discretization of Dynamical Systems Yifei Duan Liang Li Guanghua Ji Yongqiang Cai 56 4 0 22 Sep 2022
Reliable amortized variational inference with physics-based latent distribution correction Ali Siahkoohi G. Rizzuti Rafael Orozco Felix J. Herrmann 83 29 0 24 Jul 2022
Variational Flow Graphical Model Shaogang Ren Belhal Karimi Dingcheng Li Ping Li 93 4 0 06 Jul 2022
Bridging Mean-Field Games and Normalizing Flows with Trajectory Regularization Han Huang Jiajia Yu Jie Chen Rongjie Lai AI4CE 68 18 0 30 Jun 2022
Gradual Domain Adaptation via Normalizing Flows Shogo Sagawa H. Hino CLL OOD 107 10 0 23 Jun 2022
Identifiability of deep generative models without auxiliary information Bohdan Kivva Goutham Rajendran Pradeep Ravikumar Bryon Aragam DRL 117 53 0 20 Jun 2022
$C^$ -algebra Net: A New Approach Generalizing Neural Network Parameters to $C^$ -algebra Yuka Hashimoto Zhao Wang Tomoko Matsui 50 8 0 20 Jun 2022
Variational Monte Carlo Approach to Partial Differential Equations with Neural Networks M. Reh M. Gärttner 63 8 0 04 Jun 2022
PatchNR: Learning from Very Few Images by Patch Normalizing Flow Regularization Fabian Altekrüger Alexander Denker Paul Hagemann J. Hertrich Peter Maass Gabriele Steidl MedIm 86 27 0 24 May 2022
Flow-based Recurrent Belief State Learning for POMDPs Xiaoyu Chen Yao Mu Ping Luo Sheng Li Jianyu Chen 85 19 0 23 May 2022
Learning reversible symplectic dynamics Riccardo Valperga K. Webster Victoria G Klein D. Turaev J. Lamb AI4CE 41 14 0 26 Apr 2022
Universal approximation property of invertible neural networks Isao Ishikawa Takeshi Teshima Koichi Tojo Kenta Oono Masahiro Ikeda Masashi Sugiyama 107 31 0 15 Apr 2022
Universality of parametric Coupling Flows over parametric diffeomorphisms Junlong Lyu Zhitang Chen Chang Feng Wenjing Cun Shengyu Zhu Yanhui Geng Zhijie Xu Yuxiao Chen 63 3 0 07 Feb 2022
Neural Information Squeezer for Causal Emergence Jiang Zhang Kaiwei Liu CML 49 14 0 25 Jan 2022
Heavy-tailed Sampling via Transformed Unadjusted Langevin Algorithm Ye He Krishnakumar Balasubramanian Murat A. Erdogdu 83 5 0 20 Jan 2022
Rethinking Importance Weighting for Transfer Learning Nan Lu Tianyi Zhang Tongtong Fang Takeshi Teshima Masashi Sugiyama 51 11 0 19 Dec 2021
ELF: Exact-Lipschitz Based Universal Density Approximator Flow Achintya Gopal 54 1 0 13 Dec 2021