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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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Prior-Guided Residual Diffusion: Calibrated and Efficient Medical Image Segmentation Fuyou Mao Beining Wu Yanfeng Jiang Han Xue Yan Tang Hao Zhang MedIm 80 1 0 01 Sep 2025
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 147 0 0 10 Oct 2024
Probabilistic Answer Set Programming with Discrete and Continuous Random VariablesTheory and Practice of Logic Programming (TPLP), 2024 Damiano Azzolini Fabrizio Riguzzi 158 2 0 30 Sep 2024
Generalized Variable Selection Algorithms for Gaussian Process Models by LASSO-like PenaltyJournal of Computational And Graphical Statistics (JCGS), 2023 Zhiyong Hu D. Dey 169 4 0 08 Sep 2023
Capsa: A Unified Framework for Quantifying Risk in Deep Neural Networks Sadhana Lolla I. Elistratov Alejandro Perez Elaheh Ahmadi Daniela Rus Alexander Amini UQCV 74 1 0 01 Aug 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 247 73 0 14 Jan 2023
Nonlinear System Identification: Learning while respecting physical models using a sequential Monte Carlo methodIEEE Control Systems (IEEE Control Syst. Mag.), 2022 A. Wigren Johan Wågberg Fredrik Lindsten A. Wills Thomas B. Schon 166 15 0 26 Oct 2022
Borch: A Deep Universal Probabilistic Programming Language Lewis Belcher Johan Gudmundsson Michael Green BDL AI4CE UQCV 165 1 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 217 46 0 25 Aug 2022
Smoothness Analysis for Probabilistic Programs with Application to Optimised Variational Inference Wonyeol Lee Xavier Rival Hongseok Yang 297 11 0 22 Aug 2022
Foundation Posteriors for Approximate Probabilistic InferenceNeural Information Processing Systems (NeurIPS), 2022 Mike Wu Noah D. Goodman UQCV 207 6 0 19 May 2022
On Reinforcement Learning, Effect Handlers, and the State Monad Ugo Dal Lago Francesco Gavazzo Alexis Ghyselen 130 2 0 29 Mar 2022
Stochastic Perturbations of Tabular Features for Non-Deterministic Inference with Automunge Nicholas J. Teague AAML 174 1 0 18 Feb 2022
Embedded-model flows: Combining the inductive biases of model-free deep learning and explicit probabilistic modelingInternational Conference on Learning Representations (ICLR), 2021 Gianluigi Silvestri Emily Fertig David A. Moore Luca Ambrogioni BDL TPM AI4CE 345 4 0 12 Oct 2021
Unifying AI Algorithms with Probabilistic Programming using Implicitly Defined Representations Avi Pfeffer M. Harradon Joseph Campolongo S. Cvijic 159 2 0 05 Oct 2021
Supervising the Decoder of Variational Autoencoders to Improve Scientific UtilityIEEE Transactions on Signal Processing (IEEE TSP), 2021 Liyun Tu Austin Talbot Neil Gallagher David Carlson DRL 144 3 0 09 Sep 2021
Pixyz: a Python library for developing deep generative models Masahiro Suzuki T. Kaneko Y. Matsuo AI4CE 175 3 0 28 Jul 2021
JAGS, NIMBLE, Stan: a detailed comparison among Bayesian MCMC software Mario Beraha Daniel Falco A. Guglielmi 122 10 0 20 Jul 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 527 1,474 0 07 Jul 2021
Local convexity of the TAP free energy and AMP convergence for Z2-synchronizationAnnals of Statistics (Ann. Stat.), 2021 Michael Celentano Z. Fan Song Mei FedML 255 26 0 21 Jun 2021
Expectation Programming: Adapting Probabilistic Programming Systems to Estimate Expectations EfficientlyConference on Uncertainty in Artificial Intelligence (UAI), 2021 Tim Reichelt Adam Goliñski C.-H. Luke Ong Tom Rainforth TPM 155 0 0 09 Jun 2021
MINIMALIST: Mutual INformatIon Maximization for Amortized Likelihood Inference from Sampled TrajectoriesPhysical Review E (PRE), 2021 G. Isacchini Natanael Spisak Armita Nourmohammad T. Mora A. Walczak 247 0 0 03 Jun 2021
Boosting Variational Inference With Locally Adaptive Step-SizesInternational Joint Conference on Artificial Intelligence (IJCAI), 2021 Gideon Dresdner Saurav Shekhar Fabian Pedregosa Francesco Locatello Gunnar Rätsch 110 2 0 19 May 2021
Empirical Evaluation of Biased Methods for Alpha Divergence Minimization Tomas Geffner Justin Domke 164 10 0 13 May 2021
Breiman's two cultures: You don't have to choose sidesObservational Studies (OS), 2021 Andrew C. Miller N. Foti E. Fox 164 11 0 25 Apr 2021
Variational Inference for Category Recommendation in E-Commerce platforms Ramasubramanian Balasubramanian Venugopal Mani Abhinav Mathur Sushant Kumar Kannan Achan CML DRL 237 1 0 15 Apr 2021
Meta-Learning an Inference Algorithm for Probabilistic Programs Gwonsoo Che Hongseok Yang TPM 225 1 0 01 Mar 2021
Learning Proposals for Probabilistic Programs with Inference CombinatorsConference on Uncertainty in Artificial Intelligence (UAI), 2021 Sam Stites Heiko Zimmermann Hao Wu Eli Sennesh Jan-Willem van de Meent NAI 264 17 0 01 Mar 2021
BayesPerf: Minimizing Performance Monitoring Errors Using Bayesian StatisticsInternational Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS), 2021 Subho Sankar Banerjee Saurabh Jha Zbigniew T. Kalbarczyk Ravishankar Iyer 110 16 0 22 Feb 2021
Causal Mediation Analysis with Hidden ConfoundersWeb Search and Data Mining (WSDM), 2021 Lu Cheng Ruocheng Guo Huan Liu CML 268 16 0 21 Feb 2021
Automatic variational inference with cascading flowsInternational Conference on Machine Learning (ICML), 2021 Luca Ambrogioni Gianluigi Silvestri Marcel van Gerven TPM BDL 138 10 0 09 Feb 2021
BayesCard: Revitilizing Bayesian Frameworks for Cardinality Estimation Ziniu Wu Amir Shaikhha Rong Zhu Kai Zeng Yuxing Han Jingren Zhou BDL 216 31 0 29 Dec 2020
On Variational Inference for User Modeling in Attribute-Driven Collaborative Filtering Venugopal Mani Ramasubramanian Balasubramanian Sushant Kumar Abhinav Mathur Kannan Achan CML BDL EgoV 171 1 0 02 Dec 2020
Bayesian Optimization Meets Laplace Approximation for Robotic Introspection Matthias Humt Jongseo Lee Rudolph Triebel BDL UQCV 217 12 0 30 Oct 2020
Neuro-symbolic Neurodegenerative Disease Modeling as Probabilistic Programmed Deep Kernels Alexander Lavin BDL MedIm 277 11 0 16 Sep 2020
Exploring Variational Deep Q Networks A. H. Bell-Thomas 56 0 0 04 Aug 2020
Cross-Domain Medical Image Translation by Shared Latent Gaussian Mixture ModelInternational Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2020 Yingying Zhu Youbao Tang Yuxing Tang Daniel C. Elton Sungwon Lee P. J. Pickhardt Ronald M. Summers MedIm 231 24 0 14 Jul 2020
Learning Hamiltonian Monte Carlo in R Samuel Thomas W. Tu 63 42 0 29 Jun 2020
Lipschitz standardization for multivariate learning Adrián Javaloy Isabel Valera 149 0 0 26 Feb 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 277 604 0 12 Feb 2020
Automatic structured variational inferenceInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2020 Luca Ambrogioni Kate Lin Emily Fertig Sharad Vikram Max Hinne Dave Moore Marcel van Gerven BDL 264 31 0 03 Feb 2020
Big-Data Science in Porous Materials: Materials Genomics and Machine LearningChemical Reviews (Chem. Rev.), 2020 Kevin Maik Jablonka D. Ongari S. M. Moosavi B. Smit AI4CE 255 409 0 18 Jan 2020
Sampling Prediction-Matching Examples in Neural Networks: A Probabilistic Programming Approach Serena Booth Ankit J. Shah Yilun Zhou J. Shah BDL 101 1 0 09 Jan 2020
Estimating uncertainty of earthquake rupture using Bayesian neural network S. Ahamed Md Mesbah Uddin 99 6 0 21 Nov 2019
Amortized Population Gibbs Samplers with Neural Sufficient StatisticsInternational Conference on Machine Learning (ICML), 2019 Hao Wu Heiko Zimmermann Eli Sennesh T. Le Jan-Willem van de Meent 179 7 0 04 Nov 2019
Attention for Inference CompilationInternational Conference on Simulation and Modeling Methodologies, Technologies and Applications (SIMULTECH), 2019 William Harvey Andreas Munk A. G. Baydin Alexander Bergholm Frank Wood 169 9 0 25 Oct 2019
Probabilistic Surrogate Networks for Simulators with Unbounded RandomnessConference on Uncertainty in Artificial Intelligence (UAI), 2019 Andreas Munk Berend Zwartsenberg Adam Scibior A. G. Baydin Andrew Stewart G. Fernlund A. Poursartip Frank Wood TPM 208 5 0 25 Oct 2019
Streamlined Variational Inference for Linear Mixed Models with Crossed Random EffectsJournal of Computational And Graphical Statistics (JCGS), 2019 M. Menictas Gioia Di Credico M. Wand 187 15 0 04 Oct 2019
Uncertainty Quantification with Statistical Guarantees in End-to-End Autonomous Driving ControlIEEE International Conference on Robotics and Automation (ICRA), 2019 Rhiannon Michelmore Matthew Wicker Luca Laurenti L. Cardelli Y. Gal Marta Z. Kwiatkowska BDL 251 116 0 21 Sep 2019
Correcting Predictions for Approximate Bayesian InferenceAAAI Conference on Artificial Intelligence (AAAI), 2019 Tomasz Kuśmierczyk J. Sakaya Arto Klami 113 11 0 11 Sep 2019