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"

43 / 143 papers shown

Title
Compositional Score Modeling for Simulation-based Inference Tomas Geffner George Papamakarios A. Mnih 72 24 0 28 Sep 2022
Liesel: A Probabilistic Programming Framework for Developing Semi-Parametric Regression Models and Custom Bayesian Inference Algorithms Hannes Riebl P. Wiemann Thomas Kneib 8 2 0 22 Sep 2022
Improved Marginal Unbiased Score Expansion (MUSE) via Implicit Differentiation M. Millea 18 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 21 0 0 20 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 19 1 0 12 Sep 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
Strong Lensing Source Reconstruction Using Continuous Neural Fields S. Mishra-Sharma Ge Yang 69 13 0 29 Jun 2022
Neural Implicit Manifold Learning for Topology-Aware Density Estimation Brendan Leigh Ross G. Loaiza-Ganem Anthony L. Caterini Jesse C. Cresswell AI4CE 33 2 0 22 Jun 2022
Scaling multi-species occupancy models to large citizen science datasets Martin Ingram Damjan Vukcevic N. Golding 4 0 0 17 Jun 2022
Bayesian Active Learning for Scanning Probe Microscopy: from Gaussian Processes to Hypothesis Learning M. Ziatdinov Yongtao Liu K. Kelley Rama K Vasudevan Sergei V. Kalinin AI4CE 44 49 0 30 May 2022
Deterministic Langevin Monte Carlo with Normalizing Flows for Bayesian Inference R. Grumitt B. Dai U. Seljak BDL 29 12 0 27 May 2022
Tensor Program Optimization with Probabilistic Programs Junru Shao Xiyou Zhou Siyuan Feng Bohan Hou Ruihang Lai Hongyi Jin Wuwei Lin Masahiro Masuda Cody Hao Yu Tianqi Chen 37 29 0 26 May 2022
PyRelationAL: a python library for active learning research and development P. Scherer Thomas Gaudelet Alison Pouplin Alice Del Vecchio S. SurajM Oliver Bolton Jyothish Soman J. Taylor-King Lindsay Edwards KELM 19 1 0 23 May 2022
Does the Market of Citations Reward Reproducible Work? Edward Raff HAI CML 14 12 0 08 Apr 2022
Statistical Model Criticism of Variational Auto-Encoders Claartje Barkhof Wilker Aziz DRL 24 3 0 06 Apr 2022
Active learning in open experimental environments: selecting the right information channel(s) based on predictability in deep kernel learning M. Ziatdinov Yongtao Liu Sergei V. Kalinin 14 9 0 18 Mar 2022
Discovering Inductive Bias with Gibbs Priors: A Diagnostic Tool for Approximate Bayesian Inference Luca Rendsburg Agustinus Kristiadi Philipp Hennig U. V. Luxburg 16 2 0 07 Mar 2022
UncertaINR: Uncertainty Quantification of End-to-End Implicit Neural Representations for Computed Tomography Francisca Vasconcelos Bobby He Nalini Singh Yee Whye Teh BDL OOD UQCV 29 12 0 22 Feb 2022
Loss-calibrated expectation propagation for approximate Bayesian decision-making Michael J. Morais Jonathan W. Pillow 44 6 0 10 Jan 2022
Surrogate Likelihoods for Variational Annealed Importance Sampling M. Jankowiak Du Phan BDL 35 13 0 22 Dec 2021
Fast characterization of inducible regions of atrial fibrillation models with multi-fidelity Gaussian process classification Lia Gander Simone Pezzuto A. Gharaviri Rolf Krause P. Perdikaris F. Sahli Costabal 8 13 0 15 Dec 2021
ProbNum: Probabilistic Numerics in Python Jonathan Wenger Nicholas Kramer Marvin Pfortner Jonathan Schmidt Nathanael Bosch ... A. Gessner Toni Karvonen F. Briol Maren Mahsereci Philipp Hennig 52 17 0 03 Dec 2021
Toward an Idiomatic Framework for Cognitive Robotics Malte Rørmose Damgaard Rasmus Pedersen T. Bak LM&Ro 16 3 0 25 Nov 2021
Locally Differentially Private Bayesian Inference Tejas D. Kulkarni Joonas Jälkö Samuel Kaski Antti Honkela 48 2 0 27 Oct 2021
PriorVAE: Encoding spatial priors with VAEs for small-area estimation Elizaveta Semenova Yidan Xu A. Howes T. Rashid Samir Bhatt Swapnil Mishra Seth Flaxman 17 11 0 20 Oct 2021
Automatically Differentiable Random Coefficient Logistic Demand Estimation Andrew Chia 13 0 0 08 Jun 2021
Efficient and Generalizable Tuning Strategies for Stochastic Gradient MCMC Jeremie Coullon Leah F. South Christopher Nemeth 18 12 0 27 May 2021
Correlated Dynamics in Marketing Sensitivities Ryan Dew Yuhao Fan 8 1 0 23 Apr 2021
D3p -- A Python Package for Differentially-Private Probabilistic Programming Lukas Prediger Niki Loppi Samuel Kaski Antti Honkela 19 6 0 22 Mar 2021
A Probabilistic State Space Model for Joint Inference from Differential Equations and Data Jonathan Schmidt Nicholas Kramer Philipp Hennig 8 23 0 18 Mar 2021
Gaussian processes meet NeuralODEs: A Bayesian framework for learning the dynamics of partially observed systems from scarce and noisy data Mohamed Aziz Bhouri P. Perdikaris 22 20 0 04 Mar 2021
High-Dimensional Bayesian Optimization with Sparse Axis-Aligned Subspaces David Eriksson M. Jankowiak 31 134 0 27 Feb 2021
All You Need is a Good Functional Prior for Bayesian Deep Learning Ba-Hien Tran Simone Rossi Dimitrios Milios Maurizio Filippone OOD BDL 28 56 0 25 Nov 2020
Conditional independence by typing Maria I. Gorinova Andrew D. Gordon Charles Sutton Matthijs Vákár 27 14 0 22 Oct 2020
A Fully Bayesian Gradient-Free Supervised Dimension Reduction Method using Gaussian Processes Raphael Gautier Piyush Pandita Sayan Ghosh D. Mavris 10 3 0 08 Aug 2020
Estimating Model Uncertainty of Neural Networks in Sparse Information Form Jongseo Lee Matthias Humt Jianxiang Feng Rudolph Triebel BDL UQCV 38 46 0 20 Jun 2020
Rethinking Parameter Counting in Deep Models: Effective Dimensionality Revisited Wesley J. Maddox Gregory W. Benton A. Wilson 12 61 0 04 Mar 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 24 483 0 12 Feb 2020
Automatic structured variational inference L. Ambrogioni Kate Lin Emily Fertig Sharad Vikram Max Hinne Dave Moore Marcel van Gerven BDL 16 29 0 03 Feb 2020
Joint Distributions for TensorFlow Probability Dan Piponi Dave Moore Joshua V. Dillon GP 27 16 0 22 Jan 2020
FunMC: A functional API for building Markov Chains Pavel Sountsov Alexey Radul Srinivas Vasudevan 21 1 0 14 Jan 2020
Mixed Hamiltonian Monte Carlo for Mixed Discrete and Continuous Variables Guangyao Zhou 19 19 0 11 Sep 2019
A Kernel Stein Test for Comparing Latent Variable Models Heishiro Kanagawa Wittawat Jitkrittum Lester W. Mackey Kenji Fukumizu A. Gretton 13 12 0 01 Jul 2019