Pyro: Deep Universal Probabilistic Programming

18 October 2018

Papers citing "Pyro: Deep Universal Probabilistic Programming"

36 / 436 papers shown

Title
Probabilistic programming for birth-death models of evolution using an alive particle filter with delayed sampling J. Kudlicka Lawrence M. Murray F. Ronquist Thomas B. Schon 21 10 0 10 Jul 2019
Etalumis: Bringing Probabilistic Programming to Scientific Simulators at Scale A. G. Baydin Lei Shao W. Bhimji Lukas Heinrich Lawrence Meadows ... Philip Torr Victor W. Lee Kyle Cranmer P. Prabhat Frank Wood 28 55 0 08 Jul 2019
On Open-Universe Causal Reasoning D. Ibeling Thomas Icard LRM AI4CE 21 8 0 04 Jul 2019
GPU-based Parallel Computation Support for Stan Rok Cesnovar S. Bronder Davor Sluga J. Demšar Tadej Ciglarič Sean Talts Erik Štrumbelj 16 4 0 01 Jul 2019
Deployable probabilistic programming David Tolpin TPM 30 7 0 20 Jun 2019
Normalizing flows for novelty detection in industrial time series data Maximilian Schmidt M. Šimic DRL AI4TS AI4CE 16 25 0 17 Jun 2019
Near-Optimal Glimpse Sequences for Improved Hard Attention Neural Network Training William Harvey Michael Teng Frank Wood 28 4 0 13 Jun 2019
GluonTS: Probabilistic Time Series Models in Python A. Alexandrov Konstantinos Benidis Michael Bohlke-Schneider Valentin Flunkert Jan Gasthaus ... David Salinas J. Schulz Lorenzo Stella Ali Caner Türkmen Bernie Wang BDL AI4TS 18 114 0 12 Jun 2019
Kernelized Capsule Networks Taylor W. Killian Justin A. Goodwin Olivia M. Brown Sung-Hyun Son GAN 20 2 0 07 Jun 2019
Evaluating Scalable Bayesian Deep Learning Methods for Robust Computer Vision Fredrik K. Gustafsson Martin Danelljan Thomas B. Schon OOD UQCV BDL 30 295 0 04 Jun 2019
Multi-Turn Beam Search for Neural Dialogue Modeling Ilia Kulikov Jason D. Lee Kyunghyun Cho 23 3 0 01 Jun 2019
Hijacking Malaria Simulators with Probabilistic Programming Bradley Gram-Hansen Christian Schroeder de Witt Tom Rainforth Philip Torr Yee Whye Teh A. G. Baydin 25 8 0 29 May 2019
Combining Sentiment Lexica with a Multi-View Variational Autoencoder Alexander Miserlis Hoyle Lawrence Wolf-Sonkin Hanna M. Wallach Ryan Cotterell Isabelle Augenstein 11 9 0 05 Apr 2019
A semi-supervised deep learning algorithm for abnormal EEG identification Subhrajit Roy Kiran Kate Martin Hirzel 6 3 0 19 Mar 2019
Applying Probabilistic Programming to Affective Computing Desmond C. Ong Harold Soh Jamil Zaki Noah D. Goodman 19 20 0 15 Mar 2019
Variational Bayesian Optimal Experimental Design Adam Foster M. Jankowiak Eli Bingham Paul Horsfall Yee Whye Teh Tom Rainforth Noah D. Goodman 8 131 0 13 Mar 2019
Tensor Variable Elimination for Plated Factor Graphs F. Obermeyer Eli Bingham M. Jankowiak Justin T. Chiu Neeraj Pradhan Alexander M. Rush Noah D. Goodman 27 23 0 08 Feb 2019
ProBO: Versatile Bayesian Optimization Using Any Probabilistic Programming Language W. Neiswanger Kirthevasan Kandasamy Barnabás Póczós J. Schneider Eric P. Xing 33 17 0 31 Jan 2019
A Tutorial on Deep Latent Variable Models of Natural Language Yoon Kim Sam Wiseman Alexander M. Rush BDL VLM 30 42 0 17 Dec 2018
Bayesian Layers: A Module for Neural Network Uncertainty Dustin Tran Michael W. Dusenberry Mark van der Wilk Danijar Hafner UQCV BDL 19 120 0 10 Dec 2018
Joint Mapping and Calibration via Differentiable Sensor Fusion Jonathan P. Chen F. Obermeyer V. Lyapunov L. Gueguen Noah D. Goodman 21 0 0 21 Nov 2018
Simple, Distributed, and Accelerated Probabilistic Programming Like Hui Matthew Hoffman Siyuan Ma Christopher Suter Srinivas Vasudevan Alexey Radul M. Belkin Rif A. Saurous BDL 22 56 0 05 Nov 2018
Importance of Search and Evaluation Strategies in Neural Dialogue Modeling Ilia Kulikov Alexander H. Miller Kyunghyun Cho Jason Weston 29 83 0 02 Nov 2018
Closed Form Variational Objectives For Bayesian Neural Networks with a Single Hidden Layer M. Jankowiak BDL 16 2 0 02 Nov 2018
Dialogue Natural Language Inference Sean Welleck Jason Weston Arthur Szlam Kyunghyun Cho HILM 12 250 0 01 Nov 2018
Automated learning with a probabilistic programming language: Birch Lawrence M. Murray Thomas B. Schon 14 61 0 02 Oct 2018
Compiling Stan to Generative Probabilistic Languages and Extension to Deep Probabilistic Programming Guillaume Baudart Javier Burroni Martin Hirzel Louis Mandel Avraham Shinnar BDL 11 4 0 30 Sep 2018
Machine Teaching of Active Sequential Learners Tomi Peltola M. Çelikok Pedram Daee Samuel Kaski 11 25 0 08 Sep 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
Tensor Monte Carlo: particle methods for the GPU era Laurence Aitchison BDL DRL 22 13 0 22 Jun 2018
Pathwise Derivatives for Multivariate Distributions M. Jankowiak Theofanis Karaletsos 17 11 0 05 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
Revisiting Reweighted Wake-Sleep for Models with Stochastic Control Flow T. Le Adam R. Kosiorek N. Siddharth Yee Whye Teh Frank Wood BDL 9 23 0 26 May 2018
Multi-Fidelity Reinforcement Learning with Gaussian Processes Varun Suryan Nahush Gondhalekar Pratap Tokekar 11 3 0 18 Dec 2017
SaberLDA: Sparsity-Aware Learning of Topic Models on GPUs Kaiwei Li Jianfei Chen Wenguang Chen Jun Zhu 14 21 0 08 Oct 2016
Pareto Smoothed Importance Sampling Aki Vehtari Daniel Simpson Andrew Gelman Yuling Yao Jonah Gabry 15 236 0 09 Jul 2015