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Variational Inference with Normalizing Flows

21 May 2015

Danilo Jimenez Rezende

Papers citing "Variational Inference with Normalizing Flows"

50 / 2,268 papers shown

Title
SurVAE Flows: Surjections to Bridge the Gap between VAEs and Flows Didrik Nielsen P. Jaini Emiel Hoogeboom Ole Winther Max Welling TPM BDL DRL 84 92 0 06 Jul 2020
Pseudo-Rehearsal for Continual Learning with Normalizing Flows Jary Pomponi Simone Scardapane A. Uncini 48 15 0 05 Jul 2020
Differentiable Causal Discovery from Interventional Data P. Brouillard Sébastien Lachapelle Alexandre Lacoste Simon Lacoste-Julien Alexandre Drouin CML 112 191 0 03 Jul 2020
Transformations in Semi-Parametric Bayesian Synthetic Likelihood Jacob W. Priddle Christopher C. Drovandi 17 2 0 03 Jul 2020
Sliced Iterative Normalizing Flows B. Dai U. Seljak 89 37 0 01 Jul 2020
VAE-KRnet and its applications to variational Bayes Xiaoliang Wan Shuangqing Wei BDL DRL 89 13 0 29 Jun 2020
Relative gradient optimization of the Jacobian term in unsupervised deep learning Luigi Gresele G. Fissore Adrián Javaloy Bernhard Schölkopf Aapo Hyvarinen DRL 74 22 0 26 Jun 2020
Can Autonomous Vehicles Identify, Recover From, and Adapt to Distribution Shifts? Angelos Filos P. Tigas R. McAllister Nicholas Rhinehart Sergey Levine Y. Gal 83 188 0 26 Jun 2020
The Gaussian equivalence of generative models for learning with shallow neural networks Sebastian Goldt Bruno Loureiro Galen Reeves Florent Krzakala M. Mézard Lenka Zdeborová BDL 110 107 0 25 Jun 2020
SRFlow: Learning the Super-Resolution Space with Normalizing Flow Andreas Lugmayr Martin Danelljan Luc Van Gool Radu Timofte SupR DRL 113 362 0 25 Jun 2020
Learning Potentials of Quantum Systems using Deep Neural Networks Arijit Sehanobish H. Corzo Onur Kara David van Dijk 36 12 0 23 Jun 2020
Normalizing Flows Across Dimensions Edmond Cunningham Renos Zabounidis Abhinav Agrawal Ina Fiterau Daniel Sheldon DRL 66 26 0 23 Jun 2020
Locally Masked Convolution for Autoregressive Models Ajay Jain Pieter Abbeel Deepak Pathak DiffM OffRL 120 32 0 22 Jun 2020
IDF++: Analyzing and Improving Integer Discrete Flows for Lossless Compression Rianne van den Berg A. Gritsenko Mostafa Dehghani C. Sønderby Tim Salimans 92 61 0 22 Jun 2020
Deep Residual Mixture Models Perttu Hämäläinen Martin Trapp Tuure Saloheimo Arno Solin 77 8 0 22 Jun 2020
Bayesian Neural Networks: An Introduction and Survey Ethan Goan Clinton Fookes BDL UQCV 82 211 0 22 Jun 2020
Denoising Diffusion Probabilistic Models Jonathan Ho Ajay Jain Pieter Abbeel DiffM 1.0K 18,532 0 19 Jun 2020
AI Feynman 2.0: Pareto-optimal symbolic regression exploiting graph modularity S. Udrescu A. Tan Jiahai Feng Orisvaldo Neto Tailin Wu Max Tegmark 129 193 0 18 Jun 2020
Riemannian Continuous Normalizing Flows Emile Mathieu Maximilian Nickel AI4CE 151 126 0 18 Jun 2020
A Tutorial on VAEs: From Bayes' Rule to Lossless Compression Ronald Yu BDL 62 24 0 18 Jun 2020
Neural Manifold Ordinary Differential Equations Aaron Lou Derek Lim Isay Katsman Leo Huang Qingxuan Jiang Ser-Nam Lim Christopher De Sa BDL AI4CE 92 81 0 18 Jun 2020
Fine-grained Sentiment Controlled Text Generation Bidisha Samanta Mohit Agarwal Niloy Ganguly 44 4 0 17 Jun 2020
Categorical Normalizing Flows via Continuous Transformations Phillip Lippe E. Gavves BDL 138 44 0 17 Jun 2020
Longitudinal Variational Autoencoder S. Ramchandran Gleb Tikhonov Kalle Kujanpää Miika Koskinen Harri Lähdesmäki DRL CML BDL 88 37 0 17 Jun 2020
Density Deconvolution with Normalizing Flows Tim Dockhorn James A. Ritchie Yaoliang Yu Iain Murray DRL 62 5 0 16 Jun 2020
Understanding and Mitigating Exploding Inverses in Invertible Neural Networks Jens Behrmann Paul Vicol Kuan-Chieh Wang Roger C. Grosse J. Jacobsen 74 94 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 119 186 0 16 Jun 2020
Augmented Sliced Wasserstein Distances Xiongjie Chen Yongxin Yang Yunpeng Li 58 18 0 15 Jun 2020
Neural Ordinary Differential Equations on Manifolds Luca Falorsi Patrick Forré BDL AI4CE 73 33 0 11 Jun 2020
Deep Structural Causal Models for Tractable Counterfactual Inference Nick Pawlowski Daniel Coelho De Castro Ben Glocker CML MedIm 112 243 0 11 Jun 2020
Learning normalizing flows from Entropy-Kantorovich potentials Chris Finlay Augusto Gerolin Adam M. Oberman Aram-Alexandre Pooladian 102 24 0 10 Jun 2020
Probabilistic Autoencoder Vanessa Böhm U. Seljak UQCV BDL DRL 81 32 0 09 Jun 2020
SoftFlow: Probabilistic Framework for Normalizing Flow on Manifolds Hyeongju Kim Hyeonseung Lee Woohyun Kang Joun Yeop Lee N. Kim 3DPC 76 116 0 08 Jun 2020
The Power Spherical distribution Nicola De Cao Wilker Aziz 88 29 0 08 Jun 2020
Structure preserving deep learning E. Celledoni Matthias Joachim Ehrhardt Christian Etmann R. McLachlan B. Owren Carola-Bibiane Schönlieb Ferdia Sherry AI4CE 122 44 0 05 Jun 2020
Learned Factor Graphs for Inference from Stationary Time Sequences Nir Shlezinger Nariman Farsad Yonina C. Eldar Andrea J. Goldsmith 66 24 0 05 Jun 2020
Uncertainty quantification in medical image segmentation with normalizing flows Raghavendra Selvan F. Faye Jon Middleton A. Pai MedIm 99 31 0 04 Jun 2020
Equivariant Flows: Exact Likelihood Generative Learning for Symmetric Densities Jonas Köhler Leon Klein Frank Noé DRL 154 279 0 03 Jun 2020
The Convolution Exponential and Generalized Sylvester Flows Emiel Hoogeboom Victor Garcia Satorras Jakub M. Tomczak Max Welling 83 29 0 02 Jun 2020
Neural Control Variates Thomas Müller Fabrice Rousselle Jan Novák A. Keller BDL 107 56 0 02 Jun 2020
The Expressive Power of a Class of Normalizing Flow Models Zhifeng Kong Kamalika Chaudhuri TPM 82 53 0 31 May 2020
OT-Flow: Fast and Accurate Continuous Normalizing Flows via Optimal Transport Derek Onken Samy Wu Fung Xingjian Li Lars Ruthotto OT 94 162 0 29 May 2020
Joint Stochastic Approximation and Its Application to Learning Discrete Latent Variable Models Zhijian Ou Yunfu Song BDL 91 9 0 28 May 2020
Variational Neural Machine Translation with Normalizing Flows Hendra Setiawan Matthias Sperber Udhay Nallasamy Matthias Paulik DRL 58 12 0 28 May 2020
Discretize-Optimize vs. Optimize-Discretize for Time-Series Regression and Continuous Normalizing Flows Derek Onken Lars Ruthotto BDL 75 54 0 27 May 2020
MeshODE: A Robust and Scalable Framework for Mesh Deformation Jingwei Huang C. Jiang Baiqiang Leng Bin Wang Leonidas Guibas 24 7 0 23 May 2020
Deep Latent-Variable Kernel Learning Haitao Liu Yew-Soon Ong Xiaomo Jiang Xiaofang Wang BDL 59 8 0 18 May 2020
Learning Probabilistic Sentence Representations from Paraphrases Mingda Chen Kevin Gimpel 22 2 0 16 May 2020
Two equalities expressing the determinant of a matrix in terms of expectations over matrix-vector products Jascha Narain Sohl-Dickstein 23 5 0 13 May 2020
Invertible Image Rescaling Mingqing Xiao Shuxin Zheng Chang-Shu Liu Yaolong Wang Di He Guolin Ke Jiang Bian Zhouchen Lin Tie-Yan Liu SupR 95 241 0 12 May 2020