Masked Autoregressive Flow for Density Estimation

19 May 2017

Papers citing "Masked Autoregressive Flow for Density Estimation"

50 / 248 papers shown

Title
Marginalizable Density Models D. Gilboa Ari Pakman Thibault Vatter BDL 32 5 0 08 Jun 2021
Solving Schrödinger Bridges via Maximum Likelihood Francisco Vargas Pierre Thodoroff Neil D. Lawrence A. Lamacraft OT 24 131 0 03 Jun 2021
Normalizing Flows for Knockoff-free Controlled Feature Selection Derek Hansen Brian Manzo Jeffrey Regier OOD 27 5 0 03 Jun 2021
Differentially Private Normalizing Flows for Privacy-Preserving Density Estimation Chris Waites Rachel Cummings 17 15 0 25 Mar 2021
Flow-based Self-supervised Density Estimation for Anomalous Sound Detection Kota Dohi Takashi Endo Harsh Purohit Ryo Tanabe Y. Kawaguchi 22 58 0 16 Mar 2021
An Introduction to Deep Generative Modeling Lars Ruthotto E. Haber AI4CE 22 220 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 36 480 0 08 Mar 2021
Trumpets: Injective Flows for Inference and Inverse Problems K. Kothari AmirEhsan Khorashadizadeh Maarten V. de Hoop Ivan Dokmanić TPM 24 50 0 20 Feb 2021
Symplectic Adjoint Method for Exact Gradient of Neural ODE with Minimal Memory Takashi Matsubara Yuto Miyatake Takaharu Yaguchi 17 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 202 81 0 16 Feb 2021
Jacobian Determinant of Normalizing Flows Huadong Liao Jiawei He DRL 11 7 0 12 Feb 2021
Sequential Neural Posterior and Likelihood Approximation Samuel Wiqvist J. Frellsen Umberto Picchini BDL 34 33 0 12 Feb 2021
GraphDF: A Discrete Flow Model for Molecular Graph Generation Youzhi Luo Keqiang Yan Shuiwang Ji DRL 185 187 0 01 Feb 2021
Benchmarking Simulation-Based Inference Jan-Matthis Lueckmann Jan Boelts David S. Greenberg P. J. Gonçalves Jakob H. Macke 104 185 0 12 Jan 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
Regularization with Latent Space Virtual Adversarial Training Genki Osada Budrul Ahsan Revoti Prasad Bora Takashi Nishide 24 14 0 26 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
Solving high-dimensional parameter inference: marginal posterior densities & Moment Networks N. Jeffrey Benjamin Dan Wandelt 17 38 0 11 Nov 2020
Can We Trust Deep Speech Prior? Ying Shi Haolin Chen Zhiyuan Tang Lantian Li Dong Wang Jiqing Han 19 1 0 04 Nov 2020
Variational Bayesian Unlearning Q. Nguyen Bryan Kian Hsiang Low Patrick Jaillet BDL MU 19 121 0 24 Oct 2020
Neural Approximate Sufficient Statistics for Implicit Models Yanzhi Chen Dinghuai Zhang Michael U. Gutmann Aaron Courville Zhanxing Zhu 27 79 0 20 Oct 2020
Hierarchical Autoregressive Modeling for Neural Video Compression Ruihan Yang Yibo Yang Joseph Marino Stephan Mandt BDL VGen 109 46 0 19 Oct 2020
Improving Sequential Latent Variable Models with Autoregressive Flows Joseph Marino Lei Chen Jiawei He Stephan Mandt BDL AI4TS 28 12 0 07 Oct 2020
Tasks, stability, architecture, and compute: Training more effective learned optimizers, and using them to train themselves Luke Metz Niru Maheswaranathan C. Freeman Ben Poole Jascha Narain Sohl-Dickstein 22 62 0 23 Sep 2020
Variational Disentanglement for Rare Event Modeling Zidi Xiu Chenyang Tao M. Gao Connor Davis B. Goldstein Ricardo Henao CML DRL 24 6 0 17 Sep 2020
Low-rank Characteristic Tensor Density Estimation Part I: Foundations Magda Amiridi Nikos Kargas N. Sidiropoulos 19 19 0 27 Aug 2020
Neural Bridge Sampling for Evaluating Safety-Critical Autonomous Systems Aman Sinha Matthew O'Kelly Russ Tedrake John C. Duchi 39 47 0 24 Aug 2020
A Systematic Survey on Deep Generative Models for Graph Generation Xiaojie Guo Liang Zhao MedIm 44 147 0 13 Jul 2020
Variational Inference with Continuously-Indexed Normalizing Flows Anthony L. Caterini R. Cornish Dino Sejdinovic Arnaud Doucet BDL 19 19 0 10 Jul 2020
Learning Differential Equations that are Easy to Solve Jacob Kelly J. Bettencourt Matthew J. Johnson D. Duvenaud 28 111 0 09 Jul 2020
Relative gradient optimization of the Jacobian term in unsupervised deep learning Luigi Gresele G. Fissore Adrián Javaloy Bernhard Schölkopf Aapo Hyvarinen DRL 13 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 24 59 0 22 Jun 2020
STEER: Simple Temporal Regularization For Neural ODEs Arna Ghosh Harkirat Singh Behl Emilien Dupont Philip H. S. Torr Vinay P. Namboodiri BDL AI4TS 21 74 0 18 Jun 2020
Riemannian Continuous Normalizing Flows Emile Mathieu Maximilian Nickel AI4CE 27 119 0 18 Jun 2020
Likelihood-Free Inference with Deep Gaussian Processes Alexander Aushev Henri Pesonen Markus Heinonen J. Corander Samuel Kaski GP 23 10 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 92 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 19 169 0 16 Jun 2020
Probabilistic Autoencoder Vanessa Böhm U. Seljak UQCV BDL DRL 16 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 17 114 0 08 Jun 2020
The Convolution Exponential and Generalized Sylvester Flows Emiel Hoogeboom Victor Garcia Satorras Jakub M. Tomczak Max Welling 19 28 0 02 Jun 2020
Distributional Random Forests: Heterogeneity Adjustment and Multivariate Distributional Regression Domagoj Cevid Loris Michel Jeffrey Näf N. Meinshausen Peter Buhlmann 35 39 0 29 May 2020
Discretize-Optimize vs. Optimize-Discretize for Time-Series Regression and Continuous Normalizing Flows Derek Onken Lars Ruthotto BDL 24 51 0 27 May 2020
Deep Learning for Time Series Forecasting: Tutorial and Literature Survey Konstantinos Benidis Syama Sundar Rangapuram Valentin Flunkert Bernie Wang Danielle C. Maddix ... David Salinas Lorenzo Stella François-Xavier Aubet Laurent Callot Tim Januschowski AI4TS 25 176 0 21 Apr 2020
Deep Normalization for Speaker Vectors Yunqi Cai Lantian Li Dong Wang Andrew Abel 34 25 0 07 Apr 2020
Variational Inference with Vine Copulas: An efficient Approach for Bayesian Computer Model Calibration Vojtech Kejzlar T. Maiti 16 6 0 28 Mar 2020
FormulaZero: Distributionally Robust Online Adaptation via Offline Population Synthesis Aman Sinha Matthew O'Kelly Hongrui Zheng Rahul Mangharam John C. Duchi Russ Tedrake OffRL 66 26 0 09 Mar 2020
Gravitational-wave parameter estimation with autoregressive neural network flows Stephen R. Green C. Simpson J. Gair BDL 83 87 0 18 Feb 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
Multivariate Probabilistic Time Series Forecasting via Conditioned Normalizing Flows Kashif Rasul Abdul-Saboor Sheikh Ingmar Schuster Urs M. Bergmann Roland Vollgraf BDL AI4TS AI4CE 24 179 0 14 Feb 2020