Neural Autoregressive Flows

3 April 2018

Aaron Courville

Papers citing "Neural Autoregressive Flows"

50 / 101 papers shown

Title
Marginalizable Density Models D. Gilboa Ari Pakman Thibault Vatter BDL 32 5 0 08 Jun 2021
A Variational Perspective on Diffusion-Based Generative Models and Score Matching Chin-Wei Huang Jae Hyun Lim Aaron Courville DiffM 41 187 0 05 Jun 2021
Normalizing Flows for Knockoff-free Controlled Feature Selection Derek Hansen Brian Manzo Jeffrey Regier OOD 35 5 0 03 Jun 2021
Memory-Efficient Differentiable Transformer Architecture Search Yuekai Zhao Li Dong Yelong Shen Zhihua Zhang Furu Wei Weizhu Chen ViT 30 17 0 31 May 2021
Differentially Private Normalizing Flows for Privacy-Preserving Density Estimation Chris Waites Rachel Cummings 19 15 0 25 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 41 481 0 08 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 119 95 0 10 Dec 2020
RealCause: Realistic Causal Inference Benchmarking Brady Neal Chin-Wei Huang Sunand Raghupathi CML ELM 25 31 0 30 Nov 2020
Regularization with Latent Space Virtual Adversarial Training Genki Osada Budrul Ahsan Revoti Prasad Bora Takashi Nishide 30 14 0 26 Nov 2020
Very Deep VAEs Generalize Autoregressive Models and Can Outperform Them on Images R. Child BDL VLM 56 337 0 20 Nov 2020
Self Normalizing Flows Thomas Anderson Keller Jorn W. T. Peters P. Jaini Emiel Hoogeboom Patrick Forré Max Welling 30 14 0 14 Nov 2020
Causal Autoregressive Flows Ilyes Khemakhem R. Monti R. Leech Aapo Hyvarinen CML OOD AI4CE 14 108 0 04 Nov 2020
Improving Sequential Latent Variable Models with Autoregressive Flows Joseph Marino Lei Chen Jiawei He Stephan Mandt BDL AI4TS 30 12 0 07 Oct 2020
Variational Inference with Continuously-Indexed Normalizing Flows Anthony L. Caterini R. Cornish Dino Sejdinovic Arnaud Doucet BDL 24 19 0 10 Jul 2020
Relative gradient optimization of the Jacobian term in unsupervised deep learning Luigi Gresele G. Fissore Adrián Javaloy Bernhard Schölkopf Aapo Hyvarinen DRL 19 22 0 26 Jun 2020
IDF++: Analyzing and Improving Integer Discrete Flows for Lossless Compression Rianne van den Berg A. Gritsenko Mostafa Dehghani C. Sønderby Tim Salimans 27 59 0 22 Jun 2020
Advances in Black-Box VI: Normalizing Flows, Importance Weighting, and Optimization Abhinav Agrawal Daniel Sheldon Justin Domke TPM BDL 8 38 0 18 Jun 2020
Understanding and Mitigating Exploding Inverses in Invertible Neural Networks Jens Behrmann Paul Vicol Kuan-Chieh Jackson Wang Roger C. Grosse J. Jacobsen 23 93 0 16 Jun 2020
Posterior Network: Uncertainty Estimation without OOD Samples via Density-Based Pseudo-Counts Bertrand Charpentier Daniel Zügner Stephan Günnemann UQCV UD EDL BDL 25 169 0 16 Jun 2020
TraDE: Transformers for Density Estimation Rasool Fakoor Pratik Chaudhari Jonas W. Mueller Alex Smola 20 30 0 06 Apr 2020
Augmented Normalizing Flows: Bridging the Gap Between Generative Flows and Latent Variable Models Chin-Wei Huang Laurent Dinh Aaron Courville DRL 31 87 0 17 Feb 2020
Stochastic Normalizing Flows Hao Wu Jonas Köhler Frank Noé 57 176 0 16 Feb 2020
Variational Item Response Theory: Fast, Accurate, and Expressive Mike Wu R. Davis B. Domingue Chris Piech Noah D. Goodman OffRL 39 52 0 01 Feb 2020
Learning Discrete Distributions by Dequantization Emiel Hoogeboom Taco S. Cohen Jakub M. Tomczak DRL 34 31 0 30 Jan 2020
Mixed-curvature Variational Autoencoders Ondrej Skopek O. Ganea Gary Bécigneul CML DRL BDL 30 101 0 19 Nov 2019
FIS-GAN: GAN with Flow-based Importance Sampling Shiyu Yi Donglin Zhan Wenqing Zhang Zhengyang Geng Kang An Hao Wang GAN 24 3 0 06 Oct 2019
Relaxing Bijectivity Constraints with Continuously Indexed Normalising Flows R. Cornish Anthony L. Caterini George Deligiannidis Arnaud Doucet 22 2 0 30 Sep 2019
Hamiltonian Generative Networks Peter Toth Danilo Jimenez Rezende Andrew Jaegle S. Racanière Aleksandar Botev I. Higgins BDL DRL AI4CE GAN 21 216 0 30 Sep 2019
Intensity-Free Learning of Temporal Point Processes Oleksandr Shchur Marin Bilos Stephan Günnemann AI4TS 27 167 0 26 Sep 2019
Conditional Flow Variational Autoencoders for Structured Sequence Prediction Apratim Bhattacharyya M. Hanselmann Mario Fritz Bernt Schiele C. Straehle BDL DRL AI4TS 27 84 0 24 Aug 2019
Unconstrained Monotonic Neural Networks Antoine Wehenkel Gilles Louppe TPM 31 146 0 14 Aug 2019
MadMiner: Machine learning-based inference for particle physics Johann Brehmer F. Kling Irina Espejo Kyle Cranmer 21 113 0 24 Jul 2019
Copula & Marginal Flows: Disentangling the Marginal from its Joint Magnus Wiese R. Knobloch R. Korn DRL 18 21 0 07 Jul 2019
PointFlow: 3D Point Cloud Generation with Continuous Normalizing Flows Guandao Yang Xun Huang Jinwei Gu Ming Liu Serge J. Belongie Bharath Hariharan 3DPC 40 656 0 28 Jun 2019
Stochastic Neural Network with Kronecker Flow Chin-Wei Huang Ahmed Touati Pascal Vincent Gintare Karolina Dziugaite Alexandre Lacoste Aaron Courville BDL 27 8 0 10 Jun 2019
Cubic-Spline Flows Conor Durkan Artur Bekasov Iain Murray George Papamakarios TPM 48 57 0 05 Jun 2019
Effective LHC measurements with matrix elements and machine learning Johann Brehmer Kyle Cranmer Irina Espejo F. Kling Gilles Louppe J. Pavez 23 14 0 04 Jun 2019
Structured Output Learning with Conditional Generative Flows You Lu Bert Huang BDL DRL 21 72 0 30 May 2019
HINT: Hierarchical Invertible Neural Transport for Density Estimation and Bayesian Inference Jakob Kruse Gianluca Detommaso Ullrich Kothe Robert Scheichl 13 45 0 25 May 2019
Sum-of-Squares Polynomial Flow P. Jaini Kira A. Selby Yaoliang Yu TPM 22 141 0 07 May 2019
Effective Estimation of Deep Generative Language Models Tom Pelsmaeker Wilker Aziz BDL 24 27 0 17 Apr 2019
Emerging Convolutions for Generative Normalizing Flows Emiel Hoogeboom Rianne van den Berg Max Welling DRL 16 98 0 30 Jan 2019
Resampled Priors for Variational Autoencoders Matthias Bauer A. Mnih BDL DRL 16 110 0 26 Oct 2018
Good Initializations of Variational Bayes for Deep Models Simone Rossi Pietro Michiardi Maurizio Filippone BDL 17 21 0 18 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 17 851 0 02 Oct 2018
Variational Autoencoder with Implicit Optimal Priors Hiroshi Takahashi Tomoharu Iwata Yuki Yamanaka Masanori Yamada Satoshi Yagi DRL 34 61 0 14 Sep 2018
Analyzing Inverse Problems with Invertible Neural Networks Lynton Ardizzone Jakob Kruse Sebastian J. Wirkert D. Rahner E. Pellegrini R. Klessen Lena Maier-Hein Carsten Rother Ullrich Kothe 21 483 0 14 Aug 2018
Mining gold from implicit models to improve likelihood-free inference Johann Brehmer Gilles Louppe J. Pavez Kyle Cranmer AI4CE TPM 38 180 0 30 May 2018
Faithful Inversion of Generative Models for Effective Amortized Inference Stefan Webb Adam Goliñski R. Zinkov Siddharth Narayanaswamy Tom Rainforth Yee Whye Teh Frank Wood TPM 51 46 0 01 Dec 2017
A Learned Representation For Artistic Style Vincent Dumoulin Jonathon Shlens M. Kudlur GAN 214 1,156 0 24 Oct 2016