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Normalizing Flows for Probabilistic Modeling and Inference

Journal of machine learning research (JMLR), 2019

5 December 2019

George Papamakarios

Eric T. Nalisnick

Danilo Jimenez Rezende

S. Mohamed

Balaji Lakshminarayanan

TPM

AI4CE

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Papers citing "Normalizing Flows for Probabilistic Modeling and Inference"

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Title
Wavelet Flow: Fast Training of High Resolution Normalizing FlowsNeural Information Processing Systems (NeurIPS), 2020 Jason J. Yu Konstantinos G. Derpanis Marcus A. Brubaker TPM 286 45 0 26 Oct 2020
Multiscale Score Matching for Out-of-Distribution DetectionInternational Conference on Learning Representations (ICLR), 2020 Ahsan Mahmood Junier Oliva M. Styner OODD 273 33 0 25 Oct 2020
Measure Transport with Kernel Stein Discrepancy Matthew A. Fisher T. Nolan Matthew M. Graham D. Prangle Chris J. Oates OT 252 15 0 22 Oct 2020
Principled Interpolation in Normalizing Flows Samuel G. Fadel Sebastian Mair Ricardo da S. Torres Ulf Brefeld 260 3 0 22 Oct 2020
Probabilistic Character Motion Synthesis using a Hierarchical Deep Latent Variable Model Saeed Ghorbani C. Wloka Ali Etemad M. Brubaker N. Troje 3DV 136 33 0 20 Oct 2020
Deep Conditional Transformation Models Philipp F. M. Baumann Torsten Hothorn David Rügamer 293 30 0 15 Oct 2020
Sequential Likelihood-Free Inference with Neural Proposal Dongjun Kim Kyungwoo Song Yoon-Yeong Kim Yongjin Shin Wanmo Kang Il-Chul Moon Weonyoung Joo 118 2 0 15 Oct 2020
Training Invertible Linear Layers through Rank-One Perturbations Andreas Krämer Jonas Köhler Frank Noé 202 0 0 14 Oct 2020
Simulation-based inference methods for particle physics Johann Brehmer Kyle Cranmer AI4CE 270 27 0 13 Oct 2020
Adaptive and Momentum Methods on Manifolds Through Trivializations Mario Lezcano Casado 100 8 0 09 Oct 2020
A Neural Network MCMC sampler that maximizes Proposal Entropy Zengyi Li Yubei Chen Friedrich T. Sommer 216 15 0 07 Oct 2020
Scalable Normalizing Flows for Permutation Invariant Densities Marin Bilos Stephan Günnemann TPM 159 27 0 07 Oct 2020
Stein Variational Gaussian Processes Thomas Pinder Christopher Nemeth David Leslie BDL 233 7 0 25 Sep 2020
A Unifying Review of Deep and Shallow Anomaly DetectionProceedings of the IEEE (Proc. IEEE), 2020 Lukas Ruff Jacob R. Kauffmann Robert A. Vandermeulen G. Montavon Wojciech Samek Matthias Kirchler Thomas G. Dietterich Klaus-Robert Muller UQCV 540 927 0 24 Sep 2020
On the representation and learning of monotone triangular transport mapsFoundations of Computational Mathematics (FoCM), 2020 Ricardo Baptista Youssef Marzouk O. Zahm 155 62 0 22 Sep 2020
Novel and flexible parameter estimation methods for data-consistent inversion in mechanistic modelingRoyal Society Open Science (RSOS), 2020 Timothy Rumbell Jaimit Parikh J. Kozloski V. Gurev 220 9 0 17 Sep 2020
Blind Image Restoration with Flow Based Priors Leonhard Helminger M. Bernasconi Abdelaziz Djelouah Markus Gross Christopher Schroers 84 3 0 09 Sep 2020
Quasi-symplectic Langevin Variational Autoencoder Zihao Wang H. Delingette BDL DRL 229 4 0 02 Sep 2020
Langevin Cooling for Domain Translation Vignesh Srinivasan Klaus-Robert Muller Wojciech Samek Shinichi Nakajima 156 1 0 31 Aug 2020
Neural Bridge Sampling for Evaluating Safety-Critical Autonomous Systems Aman Sinha Matthew O'Kelly Russ Tedrake John C. Duchi 297 53 0 24 Aug 2020
Adaptation Algorithms for Neural Network-Based Speech Recognition: An Overview P. Bell Joachim Fainberg Ondˇrej Klejch Jinyu Li Steve Renals P. Swietojanski 292 81 0 14 Aug 2020
Learning Gradient Fields for Shape Generation Ruojin Cai Guandao Yang Hadar Averbuch-Elor Jinwei Gu Serge J. Belongie Noah Snavely B. Hariharan 3DPC 297 314 0 14 Aug 2020
CaSPR: Learning Canonical Spatiotemporal Point Cloud RepresentationsNeural Information Processing Systems (NeurIPS), 2020 Davis Rempe Tolga Birdal Yongheng Zhao Zan Gojcic Srinath Sridhar Leonidas Guibas 3DPC 293 75 0 06 Aug 2020
Normal-bundle BootstrapSIAM Journal on Mathematics of Data Science (SIMODS), 2020 Ruda Zhang R. Ghanem 220 6 0 27 Jul 2020
Time Series Source Separation with Slow Flows Edouard Pineau S. Razakarivony Thomas Bonald BDL AI4TS 131 2 0 20 Jul 2020
Discrete Point Flow Networks for Efficient Point Cloud Generation Roman Klokov Edmond Boyer Jakob Verbeek 3DPC 192 122 0 20 Jul 2020
Autoregressive flow-based causal discovery and inference R. Monti Ilyes Khemakhem Aapo Hyvarinen CML 104 4 0 18 Jul 2020
Strudel: Learning Structured-Decomposable Probabilistic CircuitsEuropean Workshop on Probabilistic Graphical Models (PGM), 2020 Meihua Dang Antonio Vergari Karen Ullrich TPM 162 36 0 18 Jul 2020
AdvFlow: Inconspicuous Black-box Adversarial Attacks using Normalizing FlowsNeural Information Processing Systems (NeurIPS), 2020 H. M. Dolatabadi S. Erfani C. Leckie AAML 268 68 0 15 Jul 2020
Relaxed-Responsibility Hierarchical Discrete VAEs M. Willetts Xenia Miscouridou Stephen J. Roberts Chris Holmes BDL DRL 215 5 0 14 Jul 2020
Estimation of Thermodynamic Observables in Lattice Field Theories with Deep Generative Models K. Nicoli Christopher J. Anders L. Funcke T. Hartung K. Jansen Pan Kessel Shinichi Nakajima Paolo Stornati AI4CE 103 3 0 14 Jul 2020
Deep composition of tensor-trains using squared inverse Rosenblatt transportsFoundations of Computational Mathematics (FoCM), 2020 Tiangang Cui S. Dolgov OT 212 39 0 14 Jul 2020
Self-Reflective Variational Autoencoder Ifigeneia Apostolopoulou Elan Rosenfeld A. Dubrawski OOD BDL DRL 114 0 0 10 Jul 2020
Learning the Prediction Distribution for Semi-Supervised Learning with Normalising Flows Ivana Balazevic Carl Allen Timothy M. Hospedales 85 0 0 06 Jul 2020
Black-box Adversarial Example Generation with Normalizing Flows H. M. Dolatabadi S. Erfani C. Leckie AAML 134 3 0 06 Jul 2020
Pseudo-Rehearsal for Continual Learning with Normalizing Flows Jary Pomponi Simone Scardapane A. Uncini 246 16 0 05 Jul 2020
Reliable Categorical Variational Inference with Mixture of Discrete Normalizing Flows Tomasz Kuśmierczyk Arto Klami BDL DRL 150 0 0 28 Jun 2020
Conditional Set Generation with Transformers Adam R. Kosiorek Hyunjik Kim Danilo Jimenez Rezende 219 43 0 26 Jun 2020
Relative gradient optimization of the Jacobian term in unsupervised deep learning Luigi Gresele G. Fissore Adrián Javaloy Bernhard Schölkopf Aapo Hyvarinen DRL 229 24 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 368 116 0 25 Jun 2020
Normalizing Flows Across Dimensions Edmond Cunningham Renos Zabounidis Abhinav Agrawal Ina Fiterau Daniel Sheldon DRL 138 28 0 23 Jun 2020
Fast and Flexible Temporal Point Processes with Triangular MapsNeural Information Processing Systems (NeurIPS), 2020 Oleksandr Shchur Nicholas Gao Marin Bilovs Stephan Günnemann 234 39 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 284 62 0 22 Jun 2020
Coupling-based Invertible Neural Networks Are Universal Diffeomorphism Approximators Takeshi Teshima Isao Ishikawa Koichi Tojo Kenta Oono Masahiro Ikeda Masashi Sugiyama 225 118 0 20 Jun 2020
Predictive Complexity Priors Eric T. Nalisnick Jonathan Gordon José Miguel Hernández-Lobato BDL UQCV 340 19 0 18 Jun 2020
STEER: Simple Temporal Regularization For Neural ODEs Arna Ghosh Harkirat Singh Behl Emilien Dupont Juil Sock Vinay P. Namboodiri BDL AI4TS 282 83 0 18 Jun 2020
Riemannian Continuous Normalizing Flows Emile Mathieu Maximilian Nickel AI4CE 305 142 0 18 Jun 2020
Advances in Black-Box VI: Normalizing Flows, Importance Weighting, and Optimization Abhinav Agrawal Daniel Sheldon Justin Domke TPM BDL 182 44 0 18 Jun 2020
MoFlow: An Invertible Flow Model for Generating Molecular Graphs Chengxi Zang Haiwei Yang BDL 245 331 0 17 Jun 2020
Density Deconvolution with Normalizing Flows Tim Dockhorn James A. Ritchie Yaoliang Yu Iain Murray DRL 158 6 0 16 Jun 2020