Composable Effects for Flexible and Accelerated Probabilistic Programming in NumPyro

24 December 2019

Papers citing "Composable Effects for Flexible and Accelerated Probabilistic Programming in NumPyro"

50 / 143 papers shown

Title
Graph-accelerated Markov Chain Monte Carlo using Approximate Samples Leo L. Duan Anirban Bhattacharya 25 1 0 25 Jan 2024
Principled Gradient-based Markov Chain Monte Carlo for Text Generation Li Du Afra Amini Lucas Torroba Hennigen Xinyan Velocity Yu Jason Eisner Holden Lee Ryan Cotterell BDL 23 1 0 29 Dec 2023
PINN surrogate of Li-ion battery models for parameter inference. Part II: Regularization and application of the pseudo-2D model M. Hassanaly Peter J. Weddle Ryan N. King Subhayan De Alireza Doostan Corey R. Randall Eric J. Dufek Andrew M. Colclasure Kandler Smith 25 6 0 28 Dec 2023
Do Bayesian Neural Networks Improve Weapon System Predictive Maintenance? Michael L. Potter Miru D. Jun 17 0 0 16 Dec 2023
RJHMC-Tree for Exploration of the Bayesian Decision Tree Posterior Jodie A. Cochrane Adrian G. Wills Sarah J. Johnson 21 2 0 04 Dec 2023
Data-driven Prior Learning for Bayesian Optimisation Sigrid Passano Hellan Christopher G. Lucas Nigel H. Goddard 26 0 0 24 Nov 2023
Diffusion models for probabilistic programming Simon Dirmeier Fernando Pérez-Cruz 58 0 0 01 Nov 2023
Uncertainty quantification and out-of-distribution detection using surjective normalizing flows Simon Dirmeier Ye Hong Yanan Xin Fernando Pérez-Cruz UQCV 28 1 0 01 Nov 2023
SigFormer: Signature Transformers for Deep Hedging Anh Tong Thanh Nguyen-Tang Dongeun Lee Toan M. Tran Jaesik Choi AIFin 24 5 0 20 Oct 2023
Towards Understanding Sycophancy in Language Models Mrinank Sharma Meg Tong Tomasz Korbak David Duvenaud Amanda Askell ... Oliver Rausch Nicholas Schiefer Da Yan Miranda Zhang Ethan Perez 213 192 0 20 Oct 2023
Neural Likelihood Approximation for Integer Valued Time Series Data Luke O'Loughlin John Maclean Andrew Black AI4TS 15 0 0 19 Oct 2023
On the Properties and Estimation of Pointwise Mutual Information Profiles Paweł Czyż Frederic Grabowski Julia E. Vogt N. Beerenwinkel Alexander Marx 24 1 0 16 Oct 2023
Fishnets: Information-Optimal, Scalable Aggregation for Sets and Graphs T. Lucas Makinen Justin Alsing Benjamin Dan Wandelt GNN FedML 24 3 0 05 Oct 2023
Reparameterized Variational Rejection Sampling M. Jankowiak Du Phan DRL BDL 24 1 0 26 Sep 2023
Detect Everything with Few Examples Xinyu Zhang Yuting Wang Abdeslam Boularias ObjD VLM 29 13 0 22 Sep 2023
Harnessing Collective Intelligence Under a Lack of Cultural Consensus Necdet Gurkan Jordan W. Suchow 25 2 0 18 Sep 2023
Choosing a Proxy Metric from Past Experiments Nilesh Tripuraneni Lee Richardson Alexander DÁmour Jacopo Soriano Steve Yadlowsky 21 7 0 14 Sep 2023
Target Detection on Hyperspectral Images Using MCMC and VI Trained Bayesian Neural Networks Daniel Ries Jason Adams J. Zollweg BDL 11 1 0 11 Aug 2023
SynJax: Structured Probability Distributions for JAX Miloš Stanojević Laurent Sartran SyDa 13 4 0 07 Aug 2023
Rapid and Scalable Bayesian AB Testing S. Chennu Andrew Maher C. Pangerl Subash Prabanantham Jae Hyeon Bae Jamie Martin Bud Goswami 35 0 0 27 Jul 2023
A Novel Application of Conditional Normalizing Flows: Stellar Age Inference with Gyrochronology P. Van-Lane J. Speagle S. Douglas 21 1 0 17 Jul 2023
Real-time whole-heart electromechanical simulations using Latent Neural Ordinary Differential Equations M. Salvador M. Strocchi Francesco Regazzoni Luca Dede' Steven Niederer A. Quarteroni AI4CE 17 3 0 08 Jun 2023
Correction of Errors in Preference Ratings from Automated Metrics for Text Generation Jan Deriu Pius von Daniken Don Tuggener Mark Cieliebak 29 2 0 06 Jun 2023
Structured Voronoi Sampling Afra Amini Li Du Ryan Cotterell DiffM 27 1 0 05 Jun 2023
An information field theory approach to Bayesian state and parameter estimation in dynamical systems Kairui Hao Ilias Bilionis 14 4 0 03 Jun 2023
Deep learning and MCMC with aggVAE for shifting administrative boundaries: mapping malaria prevalence in Kenya Elizaveta Semenova Swapnil Mishra Samir Bhatt Seth Flaxman H Juliette T Unwin 20 1 0 31 May 2023
Uncertainty and Structure in Neural Ordinary Differential Equations Katharina Ott Michael Tiemann Philipp Hennig AI4CE 26 5 0 22 May 2023
PriorCVAE: scalable MCMC parameter inference with Bayesian deep generative modelling Elizaveta Semenova Prakhar Verma Max Cairney-Leeming Arno Solin Samir Bhatt Seth Flaxman BDL 22 3 0 09 Apr 2023
Bayesian neural networks via MCMC: a Python-based tutorial Rohitash Chandra Royce Chen Joshua Simmons BDL 31 10 0 02 Apr 2023
Fluctuation without dissipation: Microcanonical Langevin Monte Carlo Jakob Robnik U. Seljak 46 6 0 31 Mar 2023
Bayesian Quantification with Black-Box Estimators Albert Ziegler Paweł Czyż UQCV 23 0 0 17 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
Federated Variational Inference Methods for Structured Latent Variable Models Conor Hassan Roberto Salomone Kerrie Mengersen BDL FedML 21 4 0 07 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 30 2 0 29 Jan 2023
Physics-informed Information Field Theory for Modeling Physical Systems with Uncertainty Quantification A. Alberts Ilias Bilionis 32 12 0 18 Jan 2023
Microcanonical Hamiltonian Monte Carlo Jakob Robnik G. Luca E. Silverstein U. Seljak 32 14 0 16 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
An Empirical Analysis of the Advantages of Finite- v.s. Infinite-Width Bayesian Neural Networks Jiayu Yao Yaniv Yacoby Beau Coker Weiwei Pan Finale Doshi-Velez 24 1 0 16 Nov 2022
Bayesian Networks for the robust and unbiased prediction of depression and its symptoms utilizing speech and multimodal data Salvatore Fara Orlaith Hickey A. Georgescu S. Goria Emilia Molimpakis N. Cummins 18 5 0 09 Nov 2022
Fully Bayesian inference for latent variable Gaussian process models Suraj Yerramilli Akshay Iyer Wei Chen D. Apley 13 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 31 15 0 27 Oct 2022
Efficient Data Mosaicing with Simulation-based Inference Andrew Gambardella Youngjun Choi Doyo Choi Jinjoon Lee 23 0 0 26 Oct 2022
Cox-Hawkes: doubly stochastic spatiotemporal Poisson processes Xenia Miscouridou Samir Bhatt G. Mohler Seth Flaxman Swapnil Mishra 19 4 0 21 Oct 2022
Transport Elliptical Slice Sampling A. Cabezas Christopher Nemeth 21 8 0 19 Oct 2022
Joint control variate for faster black-box variational inference Xi Wang Tomas Geffner Justin Domke BDL DRL 19 0 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