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Variational Inference with Normalizing Flows

21 May 2015

Danilo Jimenez Rezende

Papers citing "Variational Inference with Normalizing Flows"

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Title
GraphVF: Controllable Protein-Specific 3D Molecule Generation with Variational Flow Fangce Sun Zhihao Zhan Hongyu Guo Ming Zhang Jian Tang 75 6 0 23 Feb 2023
Comparative Study of Coupling and Autoregressive Flows through Robust Statistical Tests A. Coccaro Marco Letizia H. Reyes-González Riccardo Torre OOD 112 6 0 23 Feb 2023
Causally Disentangled Generative Variational AutoEncoder SeungHwan An Kyungwoo Song Jong-June Jeon OOD CoGe DRL CML 50 6 0 23 Feb 2023
VI-DGP: A variational inference method with deep generative prior for solving high-dimensional inverse problems Yingzhi Xia Qifeng Liao Jinglai Li 93 4 0 22 Feb 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
Diffusion Probabilistic Models for Structured Node Classification Hyosoon Jang Seonghyun Park Sangwoo Mo SungSoo Ahn DiffM 90 3 0 21 Feb 2023
Differentiable Bootstrap Particle Filters for Regime-Switching Models Wenhan Li Xiongjie Chen Wenwu Wang Victor Elvira Yunpeng Li 87 6 0 20 Feb 2023
Restoration based Generative Models Jaemoo Choi Yesom Park Myung-joo Kang DiffM AI4CE 77 5 0 20 Feb 2023
Weakly Supervised Label Learning Flows You Lu Chidubem Arachie Bert Huang 75 0 0 19 Feb 2023
An overview of differentiable particle filters for data-adaptive sequential Bayesian inference Xiongjie Chen Yunpeng Li 84 16 0 19 Feb 2023
Autocodificadores Variacionales (VAE) Fundamentos Teóricos y Aplicaciones J. D. L. Torre DRL 55 1 0 18 Feb 2023
Universality laws for Gaussian mixtures in generalized linear models Yatin Dandi Ludovic Stephan Florent Krzakala Bruno Loureiro Lenka Zdeborová FedML 102 23 0 17 Feb 2023
The Geometry of Neural Nets' Parameter Spaces Under Reparametrization Agustinus Kristiadi Felix Dangel Philipp Hennig 73 14 0 14 Feb 2023
Conditional deep generative models as surrogates for spatial field solution reconstruction with quantified uncertainty in Structural Health Monitoring applications Nicholas E. Silionis Theodora Liangou K. Anyfantis AI4CE 124 1 0 14 Feb 2023
Where to Diffuse, How to Diffuse, and How to Get Back: Automated Learning for Multivariate Diffusions Raghav Singhal Mark Goldstein Rajesh Ranganath DiffM 78 22 0 14 Feb 2023
Transport map unadjusted Langevin algorithms: learning and discretizing perturbed samplers Benjamin J. Zhang Youssef M. Marzouk K. Spiliopoulos 92 0 0 14 Feb 2023
Score Approximation, Estimation and Distribution Recovery of Diffusion Models on Low-Dimensional Data Minshuo Chen Kaixuan Huang Tuo Zhao Mengdi Wang DiffM 71 108 0 14 Feb 2023
Variational Mixture of HyperGenerators for Learning Distributions Over Functions Batuhan Koyuncu Pablo Sánchez-Martín I. Peis Pablo Martínez Olmos Isabel Valera BDL GAN DRL 91 6 0 13 Feb 2023
Variational Bayesian Neural Networks via Resolution of Singularities Susan Wei Edmund Lau BDL 71 2 0 13 Feb 2023
Differentially Private Normalizing Flows for Density Estimation, Data Synthesis, and Variational Inference with Application to Electronic Health Records Bingyue Su Yu Wang Daniele E. Schiavazzi Fang Liu 45 2 0 11 Feb 2023
Unbinned Profiled Unfolding Jay Chan Benjamin Nachman 69 7 0 10 Feb 2023
The Monge Gap: A Regularizer to Learn All Transport Maps Théo Uscidda Marco Cuturi OT 100 30 0 09 Feb 2023
Diverse Human Motion Prediction Guided by Multi-Level Spatial-Temporal Anchors Sirui Xu Yu-Xiong Wang Liangyan Gui 85 45 0 09 Feb 2023
On Sampling with Approximate Transport Maps Louis Grenioux Alain Durmus Eric Moulines Marylou Gabrié OT 70 18 0 09 Feb 2023
Fully Bayesian Autoencoders with Latent Sparse Gaussian Processes Ba-Hien Tran Babak Shahbaba Stephan Mandt Maurizio Filippone SyDa BDL UQCV 81 7 0 09 Feb 2023
Diverse Probabilistic Trajectory Forecasting with Admissibility Constraints Laura Calem H. Ben-younes P. Pérez Nicolas Thome 93 3 0 07 Feb 2023
Structured variational approximations with skew normal decomposable graphical models Roberto Salomone Xue Yu David J. Nott Robert Kohn 77 2 0 07 Feb 2023
Federated Variational Inference Methods for Structured Latent Variable Models Conor Hassan Roberto Salomone Kerrie Mengersen BDL FedML 72 4 0 07 Feb 2023
Sampling-Based Accuracy Testing of Posterior Estimators for General Inference Pablo Lemos A. Coogan Y. Hezaveh Laurence Perreault Levasseur 82 31 0 06 Feb 2023
Identifiability of latent-variable and structural-equation models: from linear to nonlinear Aapo Hyvarinen Ilyes Khemakhem R. Monti CML 118 46 0 06 Feb 2023
ShiftDDPMs: Exploring Conditional Diffusion Models by Shifting Diffusion Trajectories Zijian Zhang Zhou Zhao Jun Yu Qi Tian DiffM 45 14 0 05 Feb 2023
Improving Interpretability via Explicit Word Interaction Graph Layer Arshdeep Sekhon Hanjie Chen A. Shrivastava Zhe Wang Yangfeng Ji Yanjun Qi AI4CE MILM 70 6 0 03 Feb 2023
Fixed-kinetic Neural Hamiltonian Flows for enhanced interpretability and reduced complexity Vincent Souveton Arnaud Guillin J. Jasche G. Lavaux Manon Michel 91 3 0 03 Feb 2023
Normalizing Flow Ensembles for Rich Aleatoric and Epistemic Uncertainty Modeling Lucas Berry David Meger 71 8 0 02 Feb 2023
High-precision regressors for particle physics F. Bishara A. Paul Jennifer Dy PINN AI4CE 89 1 0 02 Feb 2023
Timewarp: Transferable Acceleration of Molecular Dynamics by Learning Time-Coarsened Dynamics Leon Klein Andrew Y. K. Foong T. E. Fjelde Bruno Mlodozeniec Marc Brockschmidt Sebastian Nowozin Frank Noé Ryota Tomioka AI4CE 151 47 0 02 Feb 2023
QCM-SGM+: Improved Quantized Compressed Sensing With Score-Based Generative Models Xiangming Meng Y. Kabashima 134 1 0 02 Feb 2023
Training Normalizing Flows with the Precision-Recall Divergence Alexandre Verine Benjamin Négrevergne Muni Sreenivas Pydi Y. Chevaleyre 41 1 0 01 Feb 2023
Two for One: Diffusion Models and Force Fields for Coarse-Grained Molecular Dynamics Marloes Arts Victor Garcia Satorras Chin-Wei Huang Daniel Zuegner Marco Federici C. Clementi Frank Noé Robert Pinsler Rianne van den Berg DiffM 118 92 0 01 Feb 2023
Automatically Marginalized MCMC in Probabilistic Programming Jinlin Lai Javier Burroni Hui Guan Daniel Sheldon 87 3 0 01 Feb 2023
Improving and generalizing flow-based generative models with minibatch optimal transport Alexander Tong Kilian Fatras Nikolay Malkin G. Huguet Yanlei Zhang Jarrid Rector-Brooks Guy Wolf Yoshua Bengio OOD DiffM OT 144 308 0 01 Feb 2023
Diffusion Models for High-Resolution Solar Forecasts Yusuke Hatanaka Yannik Glaser Geoff Galgon G. Torri Peter Sadowski DiffM 147 21 0 01 Feb 2023
IM-IAD: Industrial Image Anomaly Detection Benchmark in Manufacturing Guoyang Xie Jinbao Wang Jiaqi Liu Jiayi Lyu Yang Liu Chengjie Wang Feng Zheng Yaochu Jin VLM 120 73 0 31 Jan 2023
CHeart: A Conditional Spatio-Temporal Generative Model for Cardiac Anatomy Mengyun Qiao Shuo Wang Huaqi Qiu A. de Marvao D. O’Regan Daniel Rueckert Wenjia Bai MedIm 78 14 0 30 Jan 2023
Deep networks for system identification: a Survey G. Pillonetto Aleksandr Aravkin Daniel Gedon L. Ljung Antônio H. Ribeiro Thomas B. Schon OOD 109 45 0 30 Jan 2023
SAN: Inducing Metrizability of GAN with Discriminative Normalized Linear Layer Yuhta Takida Masaaki Imaizumi Takashi Shibuya Chieh-Hsin Lai Toshimitsu Uesaka Naoki Murata Yuki Mitsufuji GAN 111 13 0 30 Jan 2023
Pre-Training Protein Encoder via Siamese Sequence-Structure Diffusion Trajectory Prediction Zuobai Zhang Minghao Xu A. Lozano Vijil Chenthamarakshan Payel Das Jian Tang DiffM 90 22 0 28 Jan 2023
Minimizing Trajectory Curvature of ODE-based Generative Models Sangyun Lee Beomsu Kim Jong Chul Ye 147 60 0 27 Jan 2023
Learning to Generate All Feasible Actions Mirco Theile Daniele Bernardini Raphael Trumpp C. Piazza Marco Caccamo Alberto L. Sangiovanni-Vincentelli 62 2 0 26 Jan 2023
3DShape2VecSet: A 3D Shape Representation for Neural Fields and Generative Diffusion Models Biao Zhang Jiapeng Tang Matthias Niessner Peter Wonka DiffM 178 221 0 26 Jan 2023