Stochastic Variational Inference

29 June 2012

Matt Hoffman

Papers citing "Stochastic Variational Inference"

50 / 1,065 papers shown

Title
Training Bayesian Neural Networks with Sparse Subspace Variational Inference Junbo Li Zichen Miao Qiang Qiu Ruqi Zhang BDL UQCV 20 8 0 16 Feb 2024
Improved off-policy training of diffusion samplers Marcin Sendera Minsu Kim Sarthak Mittal Pablo Lemos Luca Scimeca Jarrid Rector-Brooks Alexandre Adam Yoshua Bengio Nikolay Malkin OffRL 66 17 0 07 Feb 2024
Partially Stochastic Infinitely Deep Bayesian Neural Networks Sergio Calvo-Ordoñez Matthieu Meunier Francesco Piatti Yuantao Shi BDL 37 3 0 05 Feb 2024
Position: Bayesian Deep Learning is Needed in the Age of Large-Scale AI Theodore Papamarkou Maria Skoularidou Konstantina Palla Laurence Aitchison Julyan Arbel ... David Rügamer Yee Whye Teh Max Welling Andrew Gordon Wilson Ruqi Zhang UQCV BDL 40 27 0 01 Feb 2024
Enhancing Dynamical System Modeling through Interpretable Machine Learning Augmentations: A Case Study in Cathodic Electrophoretic Deposition Christian L. Jacobsen Jiayuan Dong Mehdi Khalloufi Xun Huan Karthik Duraisamy Maryam Akram Wanjiao Liu 23 1 0 16 Jan 2024
Demystifying Variational Diffusion Models Fabio De Sousa Ribeiro Ben Glocker DiffM 25 0 0 11 Jan 2024
VI-PANN: Harnessing Transfer Learning and Uncertainty-Aware Variational Inference for Improved Generalization in Audio Pattern Recognition John Fischer Marko Orescanin Eric Eckstrand UQCV BDL 26 4 0 10 Jan 2024
Deep autoregressive modeling for land use land cover C. Krapu Mark Borsuk Ryan Calder BDL 23 0 0 02 Jan 2024
Tractable Function-Space Variational Inference in Bayesian Neural Networks Tim G. J. Rudner Zonghao Chen Yee Whye Teh Y. Gal 85 39 0 28 Dec 2023
Amortized Reparametrization: Efficient and Scalable Variational Inference for Latent SDEs Kevin Course P. Nair 29 3 0 16 Dec 2023
Joint State Estimation and Noise Identification Based on Variational Optimization Hua Lan Shijie Zhao Jinjie Hu Zengfu Wang Jing-Zhi Fu 12 1 0 15 Dec 2023
Ensemble Kalman Filtering Meets Gaussian Process SSM for Non-Mean-Field and Online Inference Zhidi Lin Yiyong Sun Feng Yin Alexandre Thiéry 29 4 0 10 Dec 2023
Mixture of Dynamical Variational Autoencoders for Multi-Source Trajectory Modeling and Separation Xiaoyu Lin Laurent Girin Xavier Alameda-Pineda 8 2 0 07 Dec 2023
Bootstrap Your Own Variance Polina Turishcheva Jason Ramapuram Sinead Williamson Dan Busbridge Eeshan Gunesh Dhekane Russ Webb UQCV 26 0 0 06 Dec 2023
Concept Drift Adaptation in Text Stream Mining Settings: A Comprehensive Review C. M. Garcia Ramon Simoes Abilio A. L. Koerich A. Britto J. P. Barddal AI4TS 44 2 0 05 Dec 2023
Deep Latent Force Models: ODE-based Process Convolutions for Bayesian Deep Learning Thomas Baldwin-McDonald Mauricio A. Álvarez 39 1 0 24 Nov 2023
Variational Elliptical Processes Maria B˙ankestad Jens Sjölund Jalil Taghia Thomas B. Schon 20 2 0 21 Nov 2023
Informative Priors Improve the Reliability of Multimodal Clinical Data Classification L. J. L. Lopez Tim G. J. Rudner Karan Singhal 45 3 0 17 Nov 2023
Uncertainty Quantification in Machine Learning for Biosignal Applications -- A Review Ivo Pascal de Jong A. Sburlea Matias Valdenegro-Toro 30 1 0 15 Nov 2023
Functional Bayesian Tucker Decomposition for Continuous-indexed Tensor Data Shikai Fang Xin Yu Zheng Wang Shibo Li R. Kirby Shandian Zhe 27 1 0 08 Nov 2023
Modelling Cellular Perturbations with the Sparse Additive Mechanism Shift Variational Autoencoder Michael D. Bereket Theofanis Karaletsos DRL 30 18 0 05 Nov 2023
Rethinking Variational Inference for Probabilistic Programs with Stochastic Support Tim Reichelt C. Ong Tom Rainforth 22 2 0 01 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
Bridging the Gap Between Variational Inference and Wasserstein Gradient Flows Mingxuan Yi Song Liu DRL 33 8 0 31 Oct 2023
On Feynman--Kac training of partial Bayesian neural networks Zheng Zhao Sebastian Mair Thomas B. Schon Jens Sjölund 35 0 0 30 Oct 2023
Optimising Distributions with Natural Gradient Surrogates Jonathan So Richard Turner 24 1 0 18 Oct 2023
Advancing Audio Emotion and Intent Recognition with Large Pre-Trained Models and Bayesian Inference Dejan Porjazovski Yaroslav Getman Tamás Grósz M. Kurimo 30 3 0 16 Oct 2023
On permutation symmetries in Bayesian neural network posteriors: a variational perspective Simone Rossi Ankit Singh T. Hannagan 32 2 0 16 Oct 2023
ZeroSwap: Data-driven Optimal Market Making in DeFi Viraj Nadkarni Jiachen Hu Ranvir Rana Chi Jin Sanjeev Kulkarni Pramod Viswanath 17 3 0 13 Oct 2023
On variational inference and maximum likelihood estimation with the λ-exponential family Thomas Guilmeau Émilie Chouzenoux Victor Elvira 30 2 0 06 Oct 2023
Accelerating optimization over the space of probability measures Shi Chen Wenxuan Wu Yuhang Yao Stephen J. Wright 32 4 0 06 Oct 2023
Coarse-to-Fine Concept Bottleneck Models Konstantinos P. Panousis Dino Ienco Diego Marcos 28 5 0 03 Oct 2023
Improvements on Scalable Stochastic Bayesian Inference Methods for Multivariate Hawkes Process Alex Ziyu Jiang Abel Rodríguez 27 1 0 26 Sep 2023
Causal Reasoning: Charting a Revolutionary Course for Next-Generation AI-Native Wireless Networks Christo Kurisummoottil Thomas Christina Chaccour Walid Saad Merouane Debbah Choong Seon Hong 26 20 0 23 Sep 2023
Evidential Deep Learning: Enhancing Predictive Uncertainty Estimation for Earth System Science Applications John S. Schreck D. Gagne Charlie Becker William E. Chapman K. Elmore ... Vanessa M. Pryzbylo Jacob T. Radford B. Saavedra Justin Willson Christopher D. Wirz BDL UD OOD UQCV EDL 15 8 0 22 Sep 2023
Neural Operator Variational Inference based on Regularized Stein Discrepancy for Deep Gaussian Processes Jian Xu Shian Du Junmei Yang Qianli Ma Delu Zeng BDL 16 1 0 22 Sep 2023
Bayesian sparsification for deep neural networks with Bayesian model reduction Dimitrije Marković K. Friston S. Kiebel BDL UQCV 38 1 0 21 Sep 2023
Total Variation Distance Meets Probabilistic Inference Arnab Bhattacharyya Sutanu Gayen Kuldeep S. Meel Dimitrios Myrisiotis A. Pavan N. V. Vinodchandran 18 4 0 17 Sep 2023
Generalized Variable Selection Algorithms for Gaussian Process Models by LASSO-like Penalty Zhiyong Hu D. Dey 23 3 0 08 Sep 2023
Distributed Variational Inference for Online Supervised Learning P. Paritosh Nikolay Atanasov Sonia Martinez 37 1 0 05 Sep 2023
Heterogeneous Multi-Task Gaussian Cox Processes Feng Zhou Quyu Kong Zhijie Deng Fengxiang He Peng Cui Jun Zhu 30 2 0 29 Aug 2023
Stochastic Variational Inference for GARCH Models Hanwen Xuan Luca Maestrini F. Chen Clara Grazian 17 2 0 29 Aug 2023
NAS-X: Neural Adaptive Smoothing via Twisting Dieterich Lawson Michael Y. Li Scott W. Linderman 20 1 0 28 Aug 2023
Sparse Linear Concept Discovery Models Konstantinos P. Panousis Dino Ienco Diego Marcos 34 15 0 21 Aug 2023
Robust Bayesian Tensor Factorization with Zero-Inflated Poisson Model and Consensus Aggregation Daniel Chafamo Vignesh Shanmugam Neriman Tokcan 14 1 0 15 Aug 2023
Natural Evolution Strategies as a Black Box Estimator for Stochastic Variational Inference Ahmad Ayaz Amin BDL DRL 21 0 0 15 Aug 2023
Towards the Development of an Uncertainty Quantification Protocol for the Natural Gas Industry Babajide Kolade 14 0 0 05 Aug 2023
Amortized Variational Inference: When and Why? C. Margossian David M. Blei 11 10 0 20 Jul 2023
Bayesian inference for data-efficient, explainable, and safe robotic motion planning: A review Chengmin Zhou Chao Wang Haseeb Hassan H. Shah Bingding Huang Pasi Fränti 3DV 38 3 0 16 Jul 2023