Pyro: Deep Universal Probabilistic Programming

18 October 2018

Papers citing "Pyro: Deep Universal Probabilistic Programming"

50 / 436 papers shown

Title
Disentangled Representation for Causal Mediation Analysis Ziqi Xu Debo Cheng Jiuyong Li Jixue Liu Lin Liu Ke Wang CML 28 9 0 19 Feb 2023
Reanalyzing L2 Preposition Learning with Bayesian Mixed Effects and a Pretrained Language Model Jakob Prange Man Ho Ivy Wong 24 2 0 16 Feb 2023
On Sampling with Approximate Transport Maps Louis Grenioux Alain Durmus Eric Moulines Marylou Gabrié OT 27 15 0 09 Feb 2023
A Benchmark on Uncertainty Quantification for Deep Learning Prognostics Luis Basora Arthur Viens M. A. Chao X. Olive UQCV BDL OOD 29 8 0 09 Feb 2023
Fortuna: A Library for Uncertainty Quantification in Deep Learning Gianluca Detommaso Alberto Gasparin Michele Donini Matthias Seeger A. Wilson Cédric Archambeau UQCV BDL 36 14 0 08 Feb 2023
Counterfactual Identifiability of Bijective Causal Models Arash Nasr-Esfahany MohammadIman Alizadeh Devavrat Shah CML BDL 35 26 0 04 Feb 2023
Automatically Marginalized MCMC in Probabilistic Programming Jinlin Lai Javier Burroni Hui Guan Daniel Sheldon 24 3 0 01 Feb 2023
Misspecification-robust Sequential Neural Likelihood for Simulation-based Inference Ryan P. Kelly David J. Nott David T. Frazier D. Warne Christopher C. Drovandi 25 10 0 31 Jan 2023
Contextual Causal Bayesian Optimisation Vahan Arsenyan Antoine Grosnit Haitham Bou-Ammar CML 32 2 0 29 Jan 2023
Scalable Gaussian Process Inference with Stan Till Hoffmann J. Onnela GP 19 4 0 21 Jan 2023
World Models and Predictive Coding for Cognitive and Developmental Robotics: Frontiers and Challenges T. Taniguchi Shingo Murata Masahiro Suzuki D. Ognibene Pablo Lanillos ... L. Jamone Tomoaki Nakamura Alejandra Ciria B. Lara G. Pezzulo 27 52 0 14 Jan 2023
Fast and Correct Gradient-Based Optimisation for Probabilistic Programming via Smoothing Basim Khajwal C.-H. Luke Ong Dominik Wagner 11 3 0 09 Jan 2023
Identifying latent distances with Finslerian geometry Alison Pouplin David Eklund Carl Henrik Ek Søren Hauberg 6 1 0 20 Dec 2022
ADEV: Sound Automatic Differentiation of Expected Values of Probabilistic Programs Alexander K. Lew Mathieu Huot S. Staton Vikash K. Mansinghka 19 20 0 13 Dec 2022
The Ordered Matrix Dirichlet for State-Space Models Niklas Stoehr Benjamin J. Radford Ryan Cotterell Aaron Schein 24 5 0 08 Dec 2022
Criteria for Classifying Forecasting Methods Tim Januschowski Jan Gasthaus Bernie Wang David Salinas Valentin Flunkert Michael Bohlke-Schneider Laurent Callot AI4TS 21 173 0 07 Dec 2022
DEL-Dock: Molecular Docking-Enabled Modeling of DNA-Encoded Libraries Kirill Shmilovich Benson Chen Theofanis Karaletos Mohammad M. Sultan 11 12 0 30 Nov 2022
Causal Inference with Conditional Instruments using Deep Generative Models Debo Cheng Ziqi Xu Jiuyong Li Lin Liu Jixue Liu T. Le CML 29 11 0 29 Nov 2022
Towards Generalizable Graph Contrastive Learning: An Information Theory Perspective Yige Yuan Bingbing Xu Huawei Shen Qi Cao Keting Cen Wen Zheng Xueqi Cheng 16 13 0 20 Nov 2022
Normalizing Flows for Hierarchical Bayesian Analysis: A Gravitational Wave Population Study David Ruhe Kaze W. K. Wong M. Cranmer Patrick Forré 16 6 0 15 Nov 2022
ALANNO: An Active Learning Annotation System for Mortals Josip Jukić Fran Jelenić Miroslav Bićanić Jan Snajder 13 4 0 11 Nov 2022
TreeFlow: probabilistic programming and automatic differentiation for phylogenetics Christiaan J. Swanepoel Mathieu Fourment Xiang Ji Hassan Nasif M. Suchard IV FrederickAMatsen A. Drummond AI4CE 8 3 0 09 Nov 2022
Black-box Coreset Variational Inference Dionysis Manousakas H. Ritter Theofanis Karaletsos BDL 21 4 0 04 Nov 2022
Fully Bayesian inference for latent variable Gaussian process models Suraj Yerramilli Akshay Iyer Wei Chen D. Apley 16 2 0 04 Nov 2022
DPVIm: Differentially Private Variational Inference Improved Joonas Jälkö Lukas Prediger Antti Honkela Samuel Kaski 34 3 0 28 Oct 2022
Improvement-Focused Causal Recourse (ICR) Gunnar Konig Timo Freiesleben Moritz Grosse-Wentrup CML 34 15 0 27 Oct 2022
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
Efficient Data Mosaicing with Simulation-based Inference Andrew Gambardella Youngjun Choi Doyo Choi Jinjoon Lee 23 0 0 26 Oct 2022
Adaptive Tuning for Metropolis Adjusted Langevin Trajectories L. Riou-Durand Pavel Sountsov Jure Vogrinc C. Margossian Samuel Power 32 6 0 21 Oct 2022
Transport Elliptical Slice Sampling A. Cabezas Christopher Nemeth 27 8 0 19 Oct 2022
Condition-number-independent convergence rate of Riemannian Hamiltonian Monte Carlo with numerical integrators Yunbum Kook Y. Lee Ruoqi Shen Santosh Vempala 38 12 0 13 Oct 2022
Robust Neural Posterior Estimation and Statistical Model Criticism Daniel Ward Patrick W Cannon Mark Beaumont Matteo Fasiolo Sebastian M. Schmon 27 36 0 12 Oct 2022
An Ordinal Latent Variable Model of Conflict Intensity Niklas Stoehr Lucas Torroba Hennigen Josef Valvoda Robert West Ryan Cotterell Aaron Schein 16 8 0 08 Oct 2022
Design Amortization for Bayesian Optimal Experimental Design Noble Kennamer Steven Walton Alexander Ihler 21 5 0 07 Oct 2022
Improved Marginal Unbiased Score Expansion (MUSE) via Implicit Differentiation M. Millea 20 4 0 21 Sep 2022
Peer-group Behaviour Analytics of Windows Authentications Events Using Hierarchical Bayesian Modelling I. Hawryluk H. Hoeltgebaum Cole Sodja Tyler Lalicker Joshua Neil 26 0 0 20 Sep 2022
Borch: A Deep Universal Probabilistic Programming Language Lewis Belcher Johan Gudmundsson Michael Green BDL AI4CE UQCV 28 0 0 13 Sep 2022
BayesLDM: A Domain-Specific Language for Probabilistic Modeling of Longitudinal Data Ka-Yee Tung Steven De La Torre Mohamed El Mistiri Rebecca Braga De Braganca Eric B. Hekler Misha Pavel D. Rivera Pedja Klasnja D. Spruijt-Metz Benjamin M. Marlin 25 1 0 12 Sep 2022
Revisiting Active Sets for Gaussian Process Decoders Pablo Moreno-Muñoz Cilie W. Feldager Søren Hauberg 16 3 0 10 Sep 2022
Investigating the Impact of Model Misspecification in Neural Simulation-based Inference Patrick W Cannon Daniel Ward Sebastian M. Schmon 25 34 0 05 Sep 2022
Learning Multiscale Non-stationary Causal Structures Gabriele DÁcunto G. D. F. Morales P. Bajardi Francesco Bonchi CML AI4TS 43 3 0 31 Aug 2022
The case for fully Bayesian optimisation in small-sample trials Yuji Saikai 19 0 0 30 Aug 2022
Fast emulation of density functional theory simulations using approximate Gaussian processes S. Stetzler M. Grosskopf E. Lawrence 23 0 0 24 Aug 2022
Deep Structural Causal Shape Models Rajat Rasal Daniel Coelho De Castro Nick Pawlowski Ben Glocker 3DV MedIm 33 12 0 23 Aug 2022
Smoothness Analysis for Probabilistic Programs with Application to Optimised Variational Inference Wonyeol Lee Xavier Rival Hongseok Yang 21 9 0 22 Aug 2022
Scalable Multi-Agent Lab Framework for Lab Optimization A. Kusne A. McDannald 16 17 0 19 Aug 2022
Generative Models: An Interdisciplinary Perspective Kris Sankaran Susan P. Holmes AI4CE 14 8 0 11 Aug 2022
One Simple Trick to Fix Your Bayesian Neural Network Piotr Tempczyk Ksawery Smoczyñski Philip Smolenski-Jensen Marek Cygan BDL MLT 8 0 0 26 Jul 2022
Language Model Cascades David Dohan Winnie Xu Aitor Lewkowycz Jacob Austin David Bieber ... Henryk Michalewski Rif A. Saurous Jascha Narain Sohl-Dickstein Kevin Patrick Murphy Charles Sutton ReLM LRM 38 99 0 21 Jul 2022
Efficient Real-world Testing of Causal Decision Making via Bayesian Experimental Design for Contextual Optimisation Desi R. Ivanova Joel Jennings Cheng Zhang Adam Foster CML 29 2 0 12 Jul 2022