Neural Autoregressive Distribution Estimation

7 May 2016

Papers citing "Neural Autoregressive Distribution Estimation"

50 / 156 papers shown

Title
Neural Density Estimation and Likelihood-free Inference George Papamakarios BDL DRL 24 44 0 29 Oct 2019
Semi-Implicit Stochastic Recurrent Neural Networks Ehsan Hajiramezanali Arman Hasanzadeh N. Duffield Krishna R. Narayanan Mingyuan Zhou Xiaoning Qian BDL 22 5 0 28 Oct 2019
Efficient training of energy-based models via spin-glass control S. Al-Fedaghi Gorka Muñoz-Gil Eloy Piñol Miguel Ángel García-March A. Acín Maciej Lewenstein Przemysław R. Grzybowski 11 8 0 03 Oct 2019
Mining for Dark Matter Substructure: Inferring subhalo population properties from strong lenses with machine learning Johann Brehmer S. Mishra-Sharma Joeri Hermans Gilles Louppe Kyle Cranmer 15 72 0 04 Sep 2019
MadMiner: Machine learning-based inference for particle physics Johann Brehmer F. Kling Irina Espejo Kyle Cranmer 21 113 0 24 Jul 2019
The Bach Doodle: Approachable music composition with machine learning at scale Cheng-Zhi Anna Huang Curtis Hawthorne Adam Roberts Monica Dinculescu James Wexler Leon Hong Jacob Howcroft 12 27 0 14 Jul 2019
Tails of Lipschitz Triangular Flows P. Jaini I. Kobyzev Yaoliang Yu Marcus A. Brubaker 14 5 0 10 Jul 2019
Bias Correction of Learned Generative Models using Likelihood-Free Importance Weighting Aditya Grover Jiaming Song Alekh Agarwal Kenneth Tran Ashish Kapoor Eric Horvitz Stefano Ermon 26 123 0 23 Jun 2019
XLNet: Generalized Autoregressive Pretraining for Language Understanding Zhilin Yang Zihang Dai Yiming Yang J. Carbonell Ruslan Salakhutdinov Quoc V. Le AI4CE 70 8,343 0 19 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
Validation of Approximate Likelihood and Emulator Models for Computationally Intensive Simulations Niccolò Dalmasso Ann B. Lee Rafael Izbicki T. Pospisil Ilmun Kim Chieh-An Lin 24 8 0 27 May 2019
Learning by stochastic serializations Pablo Strasser S. Armand Stéphane Marchand-Maillet Alexandros Kalousis 21 0 0 27 May 2019
Compression with Flows via Local Bits-Back Coding Jonathan Ho Evan Lohn Pieter Abbeel 22 52 0 21 May 2019
MoGlow: Probabilistic and controllable motion synthesis using normalising flows G. Henter Simon Alexanderson Jonas Beskow 39 97 0 16 May 2019
Best-scored Random Forest Density Estimation H. Hang Hongwei Wen 6 1 0 09 May 2019
Sum-of-Squares Polynomial Flow P. Jaini Kira A. Selby Yaoliang Yu TPM 22 141 0 07 May 2019
Supervised Anomaly Detection based on Deep Autoregressive Density Estimators Tomoharu Iwata Yuki Yamanaka 23 11 0 12 Apr 2019
Nonparametric Density Estimation for High-Dimensional Data - Algorithms and Applications Zhipeng Wang D. W. Scott 22 69 0 30 Mar 2019
Counterpoint by Convolution Cheng-Zhi Anna Huang Tim Cooijmans Adam Roberts Aaron Courville Douglas Eck BDL 27 149 0 18 Mar 2019
A Path Planning Framework for a Flying Robot in Close Proximity of Humans Hyung-Jin Yoon Christopher Widdowson Thiago Marinho R. Wang N. Hovakimyan 13 2 0 12 Mar 2019
Video Generation from Single Semantic Label Map Junting Pan Chengyu Wang Xu Jia Jing Shao Lu Sheng Junjie Yan Xiaogang Wang VGen 13 104 0 11 Mar 2019
Likelihood-free MCMC with Amortized Approximate Ratio Estimators Joeri Hermans Volodimir Begy Gilles Louppe 32 20 0 10 Mar 2019
Probabilistic Modeling for Novelty Detection with Applications to Fraud Identification Rémi Domingues AAML 17 3 0 05 Mar 2019
Deep autoregressive models for the efficient variational simulation of many-body quantum systems Or Sharir Yoav Levine Noam Wies Giuseppe Carleo Amnon Shashua 14 187 0 11 Feb 2019
Bidirectional Inference Networks: A Class of Deep Bayesian Networks for Health Profiling Hao Wang Chengzhi Mao Hao He Mingmin Zhao Tommi Jaakkola Dina Katabi BDL 24 22 0 06 Feb 2019
Exchangeable Generative Models with Flow Scans Christian Bender Kevin O'Connor Yang Li J. Garcia Manzil Zaheer Junier Oliva 3DPC 11 4 0 05 Feb 2019
A Forest from the Trees: Generation through Neighborhoods Yang Li Tianxiang Gao Junier B. Oliva 25 5 0 04 Feb 2019
Re-examination of the Role of Latent Variables in Sequence Modeling Zihang Dai Guokun Lai Yiming Yang Shinjae Yoo BDL DRL 16 4 0 04 Feb 2019
Deep Diffeomorphic Normalizing Flows Hadi Salman Payman Yadollahpour Tom Fletcher N. Batmanghelich 19 27 0 08 Oct 2018
WAIC, but Why? Generative Ensembles for Robust Anomaly Detection Hyun-Jae Choi Eric Jang Alexander A. Alemi OODD 20 82 0 02 Oct 2018
Solving Statistical Mechanics Using Variational Autoregressive Networks Dian Wu Lei Wang Pan Zhang 17 181 0 27 Sep 2018
Music Transformer Cheng-Zhi Anna Huang Ashish Vaswani Jakob Uszkoreit Noam M. Shazeer Ian Simon Curtis Hawthorne Andrew M. Dai Matthew D. Hoffman Monica Dinculescu Douglas Eck 39 470 0 12 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
Likelihood-free inference with an improved cross-entropy estimator M. Stoye Johann Brehmer Gilles Louppe J. Pavez Kyle Cranmer FedML UQCV BDL 22 48 0 02 Aug 2018
Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model A. G. Baydin Lukas Heinrich W. Bhimji Lei Shao Saeid Naderiparizi ... Philip Torr Victor W. Lee P. Prabhat Kyle Cranmer Frank Wood 26 31 0 20 Jul 2018
Temporal Difference Variational Auto-Encoder Karol Gregor George Papamakarios F. Besse Lars Buesing Theophane Weber DRL 24 126 0 08 Jun 2018
Variational Autoencoder with Arbitrary Conditioning Oleg Ivanov Michael Figurnov Dmitry Vetrov BDL DRL 19 145 0 06 Jun 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
From CDF to PDF --- A Density Estimation Method for High Dimensional Data S. Zhang 14 6 0 15 Apr 2018
Transformation Autoregressive Networks Junier B. Oliva Kumar Avinava Dubey Manzil Zaheer Barnabás Póczós Ruslan Salakhutdinov Eric Xing J. Schneider OOD 28 86 0 30 Jan 2018
Improvements to Inference Compilation for Probabilistic Programming in Large-Scale Scientific Simulators Mario Lezcano Casado A. G. Baydin David Martínez-Rubio T. Le Frank Wood ... Gilles Louppe Kyle Cranmer Karen Ng W. Bhimji P. Prabhat 42 9 0 21 Dec 2017
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 48 46 0 01 Dec 2017
An Improved Training Procedure for Neural Autoregressive Data Completion Maxime Voisin Daniel E. Ritchie 8 0 0 23 Nov 2017
Variational Bi-LSTMs Samira Shabanian Devansh Arpit Adam Trischler Yoshua Bengio DRL 33 24 0 15 Nov 2017
Z-Forcing: Training Stochastic Recurrent Networks Anirudh Goyal Alessandro Sordoni Marc-Alexandre Côté Nan Rosemary Ke Yoshua Bengio BDL 24 182 0 15 Nov 2017
Kernel Conditional Exponential Family Michael Arbel Arthur Gretton 23 25 0 15 Nov 2017
Sum-Product-Quotient Networks Or Sharir Amnon Shashua TPM 23 13 0 12 Oct 2017
Unsupervised Generative Modeling Using Matrix Product States Zhaoyu Han Jun Wang H. Fan Lei Wang Pan Zhang 22 268 0 06 Sep 2017
Recurrent Estimation of Distributions Junier B. Oliva Kumar Avinava Dubey Barnabás Póczós Eric Xing J. Schneider 22 2 0 30 May 2017
Pose Guided Person Image Generation Liqian Ma Xu Jia Qianru Sun Bernt Schiele Tinne Tuytelaars Luc Van Gool GAN 46 815 0 25 May 2017