Edward: A library for probabilistic modeling, inference, and criticism

31 October 2016

Papers citing "Edward: A library for probabilistic modeling, inference, and criticism"

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Title
Identifying latent disease factors differently expressed in patient subgroups using group factor analysis Fabio S. Ferreira John Ashburner Arabella Bouzigues Chatrin Suksasilp Lucy L. Russell ... Fermin Moreno Barbara Borroni Samuel Kaski Jonathan D. Rohrer J. Mourão-Miranda CML 51 0 0 10 Oct 2024
Nonlinear System Identification: Learning while respecting physical models using a sequential Monte Carlo method A. Wigren Johan Wågberg Fredrik Lindsten A. Wills Thomas B. Schon 24 10 0 26 Oct 2022
Borch: A Deep Universal Probabilistic Programming Language Lewis Belcher Johan Gudmundsson Michael Green BDL AI4CE UQCV 28 0 0 13 Sep 2022
NeuralUQ: A comprehensive library for uncertainty quantification in neural differential equations and operators Zongren Zou Xuhui Meng Apostolos F. Psaros George Karniadakis AI4CE 34 37 0 25 Aug 2022
Smoothness Analysis for Probabilistic Programs with Application to Optimised Variational Inference Wonyeol Lee Xavier Rival Hongseok Yang 29 9 0 22 Aug 2022
On Reinforcement Learning, Effect Handlers, and the State Monad Ugo Dal Lago Francesco Gavazzo Alexis Ghyselen 31 1 0 29 Mar 2022
Stochastic Perturbations of Tabular Features for Non-Deterministic Inference with Automunge Nicholas J. Teague AAML 38 1 0 18 Feb 2022
Unifying AI Algorithms with Probabilistic Programming using Implicitly Defined Representations Avi Pfeffer M. Harradon Joseph Campolongo S. Cvijic 24 2 0 05 Oct 2021
Supervising the Decoder of Variational Autoencoders to Improve Scientific Utility Liyun Tu Austin Talbot Neil Gallagher David Carlson DRL 32 2 0 09 Sep 2021
A Survey of Uncertainty in Deep Neural Networks J. Gawlikowski Cedrique Rovile Njieutcheu Tassi Mohsin Ali Jongseo Lee Matthias Humt ... R. Roscher Muhammad Shahzad Wen Yang R. Bamler Xiaoxiang Zhu BDL UQCV OOD 63 1,112 0 07 Jul 2021
Empirical Evaluation of Biased Methods for Alpha Divergence Minimization Tomas Geffner Justin Domke 30 9 0 13 May 2021
BayesCard: Revitilizing Bayesian Frameworks for Cardinality Estimation Ziniu Wu Amir Shaikhha Rong Zhu Kai Zeng Yuxing Han Jingren Zhou BDL 17 23 0 29 Dec 2020
Neuro-symbolic Neurodegenerative Disease Modeling as Probabilistic Programmed Deep Kernels Alexander Lavin BDL MedIm 22 9 0 16 Sep 2020
Machine Learning in Python: Main developments and technology trends in data science, machine learning, and artificial intelligence S. Raschka Joshua Patterson Corey J. Nolet AI4CE 29 485 0 12 Feb 2020
Streamlined Variational Inference for Linear Mixed Models with Crossed Random Effects M. Menictas Gioia Di Credico M. Wand 14 10 0 04 Oct 2019
Uncertainty Quantification with Statistical Guarantees in End-to-End Autonomous Driving Control Rhiannon Michelmore Matthew Wicker Luca Laurenti L. Cardelli Y. Gal Marta Z. Kwiatkowska BDL 18 105 0 21 Sep 2019
Correcting Predictions for Approximate Bayesian Inference Tomasz Kuśmierczyk J. Sakaya Arto Klami 27 10 0 11 Sep 2019
InferPy: Probabilistic Modeling with Deep Neural Networks Made Easy Javier Cózar Rafael Cabañas Antonio Salmerón A. Masegosa BDL 27 3 0 29 Aug 2019
Distributions.jl: Definition and Modeling of Probability Distributions in the JuliaStats Ecosystem Mathieu Besançon Theodore Papamarkou D. Anthoff Alex Arslan Simon Byrne Dahua Lin John Pearson GP 32 78 0 19 Jul 2019
Stochastic gradient Markov chain Monte Carlo Christopher Nemeth Paul Fearnhead BDL 27 135 0 16 Jul 2019
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 29 10 0 10 Jul 2019
Hyper-Molecules: on the Representation and Recovery of Dynamical Structures, with Application to Flexible Macro-Molecular Structures in Cryo-EM Roy R. Lederman Joakim Andén A. Singer 37 30 0 02 Jul 2019
Physics-Informed Probabilistic Learning of Linear Embeddings of Non-linear Dynamics With Guaranteed Stability Shaowu Pan Karthik Duraisamy 23 136 0 09 Jun 2019
The Medical Deconfounder: Assessing Treatment Effects with Electronic Health Records Linying Zhang Yixin Wang A. Ostropolets J. J. Mulgrave David M. Blei G. Hripcsak BDL CML 15 1 0 03 Apr 2019
Statistical Guarantees for the Robustness of Bayesian Neural Networks L. Cardelli Marta Kwiatkowska Luca Laurenti Nicola Paoletti A. Patané Matthew Wicker AAML 31 54 0 05 Mar 2019
Unsupervised learning with contrastive latent variable models Kristen A. Severson S. Ghosh Kenney Ng SSL DRL 27 38 0 14 Nov 2018
Probabilistic Programming with Densities in SlicStan: Efficient, Flexible and Deterministic Maria I. Gorinova Andrew D. Gordon Charles Sutton 25 23 0 02 Nov 2018
An Introduction to Probabilistic Programming Jan-Willem van de Meent Brooks Paige Hongseok Yang Frank Wood GP 30 196 0 27 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 34 31 0 20 Jul 2018
Quasi-Monte Carlo Variational Inference Alexander K. Buchholz F. Wenzel Stephan Mandt BDL 30 58 0 04 Jul 2018
Non-Parametric Calibration of Probabilistic Regression Hao Song Meelis Kull Peter A. Flach 9 4 0 20 Jun 2018
INFERNO: Inference-Aware Neural Optimisation P. D. Castro T. Dorigo 24 47 0 12 Jun 2018
Boosting Black Box Variational Inference Francesco Locatello Gideon Dresdner Rajiv Khanna Isabel Valera Gunnar Rätsch 42 31 0 06 Jun 2018
Discrete-Continuous Mixtures in Probabilistic Programming: Generalized Semantics and Inference Algorithms Yi Wu Siddharth Srivastava N. Hay S. Du Stuart J. Russell 31 25 0 06 Jun 2018
Wasserstein Variational Inference L. Ambrogioni Umut Güçlü Yağmur Güçlütürk Max Hinne E. Maris Marcel van Gerven BDL DRL 19 42 0 29 May 2018
The Blessings of Multiple Causes Yixin Wang David M. Blei AI4CE CML 24 284 0 17 May 2018
Alpha-Beta Divergence For Variational Inference Jean-Baptiste Regli Ricardo M. A. Silva BDL 9 24 0 02 May 2018
Generating Multi-Agent Trajectories using Programmatic Weak Supervision Eric Zhan Stephan Zheng Yisong Yue Long Sha P. Lucey 25 88 0 20 Mar 2018
Symbol Emergence in Cognitive Developmental Systems: a Survey T. Taniguchi Emre Ugur Matej Hoffmann L. Jamone Takayuki Nagai ... Toshihiko Matsuka N. Iwahashi Erhan Öztop J. Piater Florentin Wörgötter 31 90 0 26 Jan 2018
Sequential Preference-Based Optimization Ian Dewancker Jakob Bauer M. McCourt 38 6 0 09 Jan 2018
TensorFlow Distributions Joshua V. Dillon I. Langmore Dustin Tran E. Brevdo Srinivas Vasudevan David A. Moore Brian Patton Alexander A. Alemi Matt Hoffman Rif A. Saurous GP 46 346 0 28 Nov 2017
Advances in Variational Inference Cheng Zhang Judith Butepage Hedvig Kjellström Stephan Mandt BDL 38 684 0 15 Nov 2017
Control Variates for Stochastic Gradient MCMC Jack Baker Paul Fearnhead E. Fox Christopher Nemeth BDL 37 101 0 16 Jun 2017
Deep Learning: A Bayesian Perspective Nicholas G. Polson Vadim Sokolov BDL 41 115 0 01 Jun 2017
Proximity Variational Inference Jaan Altosaar Rajesh Ranganath David M. Blei BDL 10 21 0 24 May 2017
Causal Effect Inference with Deep Latent-Variable Models Christos Louizos Uri Shalit Joris Mooij David Sontag R. Zemel Max Welling CML BDL 69 732 0 24 May 2017
Sticking the Landing: Simple, Lower-Variance Gradient Estimators for Variational Inference Geoffrey Roeder Yuhuai Wu David Duvenaud BDL 30 196 0 27 Mar 2017
Dynamic Bernoulli Embeddings for Language Evolution Maja R. Rudolph David M. Blei BDL 22 34 0 23 Mar 2017
Hierarchical Implicit Models and Likelihood-Free Variational Inference Dustin Tran Rajesh Ranganath David M. Blei VLM GAN 30 100 0 28 Feb 2017
Deep Probabilistic Programming Dustin Tran Matthew D. Hoffman Rif A. Saurous E. Brevdo Kevin Patrick Murphy David M. Blei BDL 36 193 0 13 Jan 2017