Variational Inference with Normalizing Flows

21 May 2015

Danilo Jimenez Rezende

Papers citing "Variational Inference with Normalizing Flows"

50 / 936 papers shown

Title
CaloFlow: Fast and Accurate Generation of Calorimeter Showers with Normalizing Flows Claudius Krause David Shih AI4CE 36 81 0 09 Jun 2021
Bayesian Bellman Operators M. Fellows Kristian Hartikainen Shimon Whiteson OffRL 42 15 0 09 Jun 2021
Flow Network based Generative Models for Non-Iterative Diverse Candidate Generation Emmanuel Bengio Moksh Jain Maksym Korablyov Doina Precup Yoshua Bengio 49 312 0 08 Jun 2021
On Memorization in Probabilistic Deep Generative Models G. V. D. Burg Christopher K. I. Williams TDI 25 59 0 06 Jun 2021
On Training Sample Memorization: Lessons from Benchmarking Generative Modeling with a Large-scale Competition C. Bai Hsuan-Tien Lin Colin Raffel Wendy Kan 18 34 0 06 Jun 2021
Integrating Expert ODEs into Neural ODEs: Pharmacology and Disease Progression Zhaozhi Qian W. Zame L. Fleuren Paul Elbers M. Schaar OOD 22 53 0 05 Jun 2021
Hierarchical Video Generation for Complex Data Lluis Castrejon Nicolas Ballas Aaron Courville VGen 22 4 0 04 Jun 2021
Semi-Empirical Objective Functions for MCMC Proposal Optimization Chris Cannella Vahid Tarokh 31 1 0 03 Jun 2021
Latent Space Refinement for Deep Generative Models R. Winterhalder Marco Bellagente Benjamin Nachman BDL GAN DRL DiffM 20 27 0 01 Jun 2021
Fourier Space Losses for Efficient Perceptual Image Super-Resolution Dario Fuoli Luc Van Gool Radu Timofte 22 112 0 01 Jun 2021
Optimizing Functionals on the Space of Probabilities with Input Convex Neural Networks David Alvarez-Melis Yair Schiff Youssef Mroueh 40 53 0 01 Jun 2021
Transformation Models for Flexible Posteriors in Variational Bayes Sefan Hörtling Daniel Dold Oliver Durr Beate Sick 23 0 0 01 Jun 2021
Hybrid Generative Models for Two-Dimensional Datasets Hoda Shajari Jaemoon Lee Sanjay Ranka Anand Rangarajan MedIm 24 0 0 01 Jun 2021
Geometric variational inference Philipp Frank R. Leike T. Ensslin 45 22 0 21 May 2021
Variational Gaussian Topic Model with Invertible Neural Projections Rui Wang Deyu Zhou Yuxuan Xiong Haiping Huang BDL 27 3 0 21 May 2021
E(n) Equivariant Normalizing Flows Victor Garcia Satorras Emiel Hoogeboom F. Fuchs Ingmar Posner Max Welling BDL 37 170 0 19 May 2021
Priors in Bayesian Deep Learning: A Review Vincent Fortuin UQCV BDL 38 124 0 14 May 2021
Grad-TTS: A Diffusion Probabilistic Model for Text-to-Speech Vadim Popov Ivan Vovk Vladimir Gogoryan Tasnima Sadekova Mikhail Kudinov DiffM 61 515 0 13 May 2021
Generative Adversarial Networks (GANs) in Networking: A Comprehensive Survey & Evaluation Hojjat Navidan P. Moshiri M. Nabati Reza Shahbazian S. Ghorashi V. Shah-Mansouri David Windridge 15 84 0 10 May 2021
COMISR: Compression-Informed Video Super-Resolution Yinxiao Li Pengchong Jin Feng Yang Ce Liu Ming-Hsuan Yang P. Milanfar SupR 34 38 0 04 May 2021
Data Augmentation in High Dimensional Low Sample Size Setting Using a Geometry-Based Variational Autoencoder Clément Chadebec Elina Thibeau-Sutre Ninon Burgos S. Allassonnière 48 63 0 30 Apr 2021
PCFGs Can Do Better: Inducing Probabilistic Context-Free Grammars with Many Symbols Aaron Courville Yanpeng Zhao Kewei Tu 23 22 0 28 Apr 2021
From Human Explanation to Model Interpretability: A Framework Based on Weight of Evidence David Alvarez-Melis Harmanpreet Kaur Hal Daumé Hanna M. Wallach Jennifer Wortman Vaughan FAtt 56 28 0 27 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 83 143 0 21 Apr 2021
Class-Incremental Learning with Generative Classifiers Gido M. van de Ven Zhe Li A. Tolias BDL 50 58 0 20 Apr 2021
Learning by example: fast reliability-aware seismic imaging with normalizing flows Ali Siahkoohi Felix J. Herrmann OOD 29 13 0 13 Apr 2021
Understanding Event-Generation Networks via Uncertainties Marco Bellagente Manuel Haussmann Michel Luchmann Tilman Plehn BDL 41 55 0 09 Apr 2021
Multilevel Stein variational gradient descent with applications to Bayesian inverse problems Terrence Alsup Luca Venturi Benjamin Peherstorfer 26 5 0 05 Apr 2021
AgentFormer: Agent-Aware Transformers for Socio-Temporal Multi-Agent Forecasting Ye Yuan Xinshuo Weng Yanglan Ou Kris Kitani AI4TS 45 442 0 25 Mar 2021
Continuous normalizing flows on manifolds Luca Falorsi BDL AI4CE 30 10 0 14 Mar 2021
VCNet and Functional Targeted Regularization For Learning Causal Effects of Continuous Treatments Lizhen Nie Mao Ye Qiang Liu D. Nicolae CML 25 69 0 14 Mar 2021
An Introduction to Deep Generative Modeling Lars Ruthotto E. Haber AI4CE 33 221 0 09 Mar 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 48 485 0 08 Mar 2021
Generating Images with Sparse Representations C. Nash Jacob Menick Sander Dieleman Peter W. Battaglia 33 201 0 05 Mar 2021
D'ya like DAGs? A Survey on Structure Learning and Causal Discovery M. Vowels Necati Cihan Camgöz Richard Bowden CML 43 297 0 03 Mar 2021
Countering Malicious DeepFakes: Survey, Battleground, and Horizon Felix Juefei Xu Run Wang Yihao Huang Qing Guo Lei Ma Yang Liu AAML 33 132 0 27 Feb 2021
A Hybrid Approximation to the Marginal Likelihood Eric Chuu D. Pati A. Bhattacharya 19 2 0 24 Feb 2021
Improving Lossless Compression Rates via Monte Carlo Bits-Back Coding Yangjun Ruan Karen Ullrich Daniel de Souza Severo James Townsend Ashish Khisti Arnaud Doucet Alireza Makhzani Chris J. Maddison 18 25 0 22 Feb 2021
Learning Neural Generative Dynamics for Molecular Conformation Generation Minkai Xu Shitong Luo Yoshua Bengio Jian-wei Peng Jian Tang AI4CE 30 116 0 20 Feb 2021
Symplectic Adjoint Method for Exact Gradient of Neural ODE with Minimal Memory Takashi Matsubara Yuto Miyatake Takaharu Yaguchi 23 23 0 19 Feb 2021
DEUP: Direct Epistemic Uncertainty Prediction Salem Lahlou Moksh Jain Hadi Nekoei V. Butoi Paul Bertin Jarrid Rector-Brooks Maksym Korablyov Yoshua Bengio PER UQLM UQCV UD 212 81 0 16 Feb 2021
Annealed Flow Transport Monte Carlo Michael Arbel A. G. Matthews Arnaud Doucet 45 70 0 15 Feb 2021
Jacobian Determinant of Normalizing Flows Huadong Liao Jiawei He DRL 19 7 0 12 Feb 2021
Sequential Neural Posterior and Likelihood Approximation Samuel Wiqvist J. Frellsen Umberto Picchini BDL 39 33 0 12 Feb 2021
Argmax Flows and Multinomial Diffusion: Learning Categorical Distributions Emiel Hoogeboom Didrik Nielsen P. Jaini Patrick Forré Max Welling DiffM 222 402 0 10 Feb 2021
Sampling in Combinatorial Spaces with SurVAE Flow Augmented MCMC P. Jaini Didrik Nielsen Max Welling BDL 43 10 0 04 Feb 2021
A Living Review of Machine Learning for Particle Physics Matthew Feickert Benjamin Nachman KELM AI4CE 39 178 0 02 Feb 2021
GraphDF: A Discrete Flow Model for Molecular Graph Generation Youzhi Luo Keqiang Yan Shuiwang Ji DRL 185 190 0 01 Feb 2021
Neural representation and generation for RNA secondary structures Zichao Yan William L. Hamilton Mathieu Blanchette 40 2 0 01 Feb 2021
Convolutional conditional neural processes for local climate downscaling Anna Vaughan Will Tebbutt J. S. Hosking Richard Turner BDL 28 47 0 20 Jan 2021