Pyro: Deep Universal Probabilistic Programming

18 October 2018

Papers citing "Pyro: Deep Universal Probabilistic Programming"

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Title
High-Dimensional Bayesian Optimization with Sparse Axis-Aligned Subspaces David Eriksson M. Jankowiak 31 134 0 27 Feb 2021
Truncated Log-concave Sampling with Reflective Hamiltonian Monte Carlo Apostolos Chalkis Vissarion Fisikopoulos Marios Papachristou Elias P. Tsigaridas 19 8 0 25 Feb 2021
SBI: A Simulation-Based Test of Identifiability for Bayesian Causal Inference Sam Witty David D. Jensen Vikash K. Mansinghka CML 13 3 0 23 Feb 2021
Do-calculus enables estimation of causal effects in partially observed biomolecular pathways Sara Mohammad-Taheri Jeremy Zucker C. Hoyt Karen Sachs Vartika Tewari Robert Osazuwa Ness and Olga Vitek 31 0 0 12 Feb 2021
HNPE: Leveraging Global Parameters for Neural Posterior Estimation Pedro L. C. Rodrigues Thomas Moreau Gilles Louppe Alexandre Gramfort 36 11 0 12 Feb 2021
Automatic variational inference with cascading flows L. Ambrogioni Gianluigi Silvestri Marcel van Gerven TPM BDL 19 8 0 09 Feb 2021
Variational Bayes survival analysis for unemployment modelling P. Boškoski M. Perne M. Ramesa Biljana Mileva-Boshkoska CML 19 10 0 03 Feb 2021
Semi-supervised source localization in reverberant environments with deep generative modeling Michael J. Bianco Sharon Gannot Efren Fernandez-Grande Peter Gerstoft 13 21 0 26 Jan 2021
Leveraging Structured Biological Knowledge for Counterfactual Inference: a Case Study of Viral Pathogenesis Jeremy Zucker Kaushal Paneri Sara Mohammad-Taheri Somya Bhargava Pallavi Kolambkar ... J. Teuton Charles Tapley Hoyt Kristie L. Oxford Robert Osazuwa Ness O. Vitek CML 13 13 0 13 Jan 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
Control-Data Separation and Logical Condition Propagation for Efficient Inference on Probabilistic Programs I. Hasuo Yuichiro Oyabu Clovis Eberhart Kohei Suenaga Kenta Cho Shin-ya Katsumata TPM 22 3 0 05 Jan 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
Distilled Thompson Sampling: Practical and Efficient Thompson Sampling via Imitation Learning Hongseok Namkoong Sam Daulton E. Bakshy OffRL 8 6 0 29 Nov 2020
Direct Evolutionary Optimization of Variational Autoencoders With Binary Latents E. Guiraud Jakob Drefs Jörg Lücke DRL 35 3 0 27 Nov 2020
Learning a Deep Generative Model like a Program: the Free Category Prior Eli Sennesh NAI BDL 9 0 0 22 Nov 2020
Privug: Using Probabilistic Programming for Quantifying Leakage in Privacy Risk Analysis Raúl Pardo Willard Rafnsson Christian W. Probst Andrzej Wasowski PILM 9 4 0 17 Nov 2020
Bayesian model of electrical heating disaggregation Franccois Culiere Laetitia Leduc A. Belikov 12 10 0 11 Nov 2020
Survival prediction and risk estimation of Glioma patients using mRNA expressions Navodini Wijethilake D. Meedeniya Charith D. Chitraranjan I. Perera 9 11 0 02 Nov 2020
Bayesian Optimization Meets Laplace Approximation for Robotic Introspection Matthias Humt Jongseo Lee Rudolph Triebel BDL UQCV 20 11 0 30 Oct 2020
Accelerating Metropolis-Hastings with Lightweight Inference Compilation Feynman T. Liang Nimar S. Arora N. Tehrani Y. Li Michael Tingley E. Meijer 12 0 0 23 Oct 2020
Measure Transport with Kernel Stein Discrepancy Matthew A. Fisher T. Nolan Matthew M. Graham D. Prangle Chris J. Oates OT 31 15 0 22 Oct 2020
Semi-parametric $γ$ -ray modeling with Gaussian processes and variational inference S. Mishra-Sharma Kyle Cranmer MedIm 21 7 0 20 Oct 2020
Bayesian Inference for Optimal Transport with Stochastic Cost Anton Mallasto Markus Heinonen Samuel Kaski OT 44 1 0 19 Oct 2020
Scaling Hamiltonian Monte Carlo Inference for Bayesian Neural Networks with Symmetric Splitting Adam D. Cobb Brian Jalaian BDL 14 73 0 14 Oct 2020
Flexible mean field variational inference using mixtures of non-overlapping exponential families J. Spence 17 4 0 14 Oct 2020
Targeted VAE: Variational and Targeted Learning for Causal Inference M. Vowels Necati Cihan Camgöz Richard Bowden BDL OOD CML 11 8 0 28 Sep 2020
Probabilistic Machine Learning for Healthcare Irene Y. Chen Shalmali Joshi Marzyeh Ghassemi Rajesh Ranganath OOD 6 51 0 23 Sep 2020
Independent finite approximations for Bayesian nonparametric inference Tin D. Nguyen Jonathan H. Huggins L. Masoero Lester W. Mackey Tamara Broderick TPM 15 4 0 22 Sep 2020
Modeling Score Distributions and Continuous Covariates: A Bayesian Approach Mel McCurrie Hamish Nicholson Walter J. Scheirer Samuel E. Anthony 6 1 0 21 Sep 2020
Neuro-symbolic Neurodegenerative Disease Modeling as Probabilistic Programmed Deep Kernels Alexander Lavin BDL MedIm 6 9 0 16 Sep 2020
Generalized Multi-Output Gaussian Process Censored Regression Daniele Gammelli Kasper Pryds Rolsted Dario Pacino Filipe Rodrigues 6 14 0 10 Sep 2020
Training Multimodal Systems for Classification with Multiple Objectives Jason Armitage Shramana Thakur Rishi Tripathi Jens Lehmann M. Maleshkova 24 1 0 26 Aug 2020
A Fully Bayesian Gradient-Free Supervised Dimension Reduction Method using Gaussian Processes Raphael Gautier Piyush Pandita Sayan Ghosh D. Mavris 12 3 0 08 Aug 2020
PClean: Bayesian Data Cleaning at Scale with Domain-Specific Probabilistic Programming Alexander K. Lew Monica Agrawal David Sontag Vikash K. Mansinghka 6 26 0 23 Jul 2020
Automating Involutive MCMC using Probabilistic and Differentiable Programming Marco F. Cusumano-Towner Alexander K. Lew Vikash K. Mansinghka 6 16 0 20 Jul 2020
Analysis of Bayesian Networks via Prob-Solvable Loops E. Bartocci L. Kovács Miroslav Stankovič TPM 22 12 0 18 Jul 2020
Smart Choices and the Selection Monad M. Abadi G. Plotkin 17 3 0 17 Jul 2020
Hands-on Bayesian Neural Networks -- a Tutorial for Deep Learning Users Laurent Valentin Jospin Wray L. Buntine F. Boussaïd Hamid Laga Bennamoun OOD BDL UQCV 13 610 0 14 Jul 2020
Verification of ML Systems via Reparameterization Jean-Baptiste Tristan Joseph Tassarotti Koundinya Vajjha Michael L. Wick A. Banerjee AAML 9 6 0 14 Jul 2020
BaCOUn: Bayesian Classifers with Out-of-Distribution Uncertainty Théo Guénais Dimitris Vamvourellis Yaniv Yacoby Finale Doshi-Velez Weiwei Pan UQCV 6 13 0 12 Jul 2020
SurVAE Flows: Surjections to Bridge the Gap between VAEs and Flows Didrik Nielsen P. Jaini Emiel Hoogeboom Ole Winther Max Welling TPM BDL DRL 23 88 0 06 Jul 2020
A Competence-aware Curriculum for Visual Concepts Learning via Question Answering Qing Li Siyuan Huang Yining Hong Song-Chun Zhu 22 29 0 03 Jul 2020
Towards Adaptive Benthic Habitat Mapping J. Shields Oscar Pizarro Stefan B. Williams 14 14 0 20 Jun 2020
Deep Structural Causal Models for Tractable Counterfactual Inference Nick Pawlowski Daniel Coelho De Castro Ben Glocker CML MedIm 33 229 0 11 Jun 2020
Recurrent Flow Networks: A Recurrent Latent Variable Model for Density Modelling of Urban Mobility Daniele Gammelli Filipe Rodrigues 13 1 0 09 Jun 2020
Semi-supervised source localization with deep generative modeling Michael J. Bianco Sharon Gannot Peter Gerstoft DRL 16 21 0 27 May 2020
Bayesian Neural Networks at Scale: A Performance Analysis and Pruning Study Himanshu Sharma Elise Jennings BDL 27 3 0 23 May 2020
Simulation-Based Inference for Global Health Decisions Christian Schroeder de Witt Bradley Gram-Hansen Nantas Nardelli Andrew Gambardella R. Zinkov ... N. Siddharth A. B. Espinosa-González A. Darzi Philip Torr A. G. Baydin AI4CE 23 4 0 14 May 2020
When and How to Lift the Lockdown? Global COVID-19 Scenario Analysis and Policy Assessment using Compartmental Gaussian Processes Zhaozhi Qian Ahmed Alaa M. Schaar 9 33 0 13 May 2020
Incorporating structured assumptions with probabilistic graphical models in fMRI data analysis M. Cai Michael Shvartsman Anqi Wu Hejia Zhang Xia Zhu AI4CE 19 12 0 11 May 2020