Bayes-Newton Methods for Approximate Bayesian Inference with PSD
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Bayes-Newton Methods for Approximate Bayesian Inference with PSD Guarantees

2 November 2021

William J. Wilkinson

Simo Särkkä

Arno Solin

Papers citing "Bayes-Newton Methods for Approximate Bayesian Inference with PSD Guarantees"

10 / 10 papers shown

Title
Physics-Informed Variational State-Space Gaussian Processes Oliver Hamelijnck Arno Solin Theodoros Damoulas 16 0 0 20 Sep 2024
Fearless Stochasticity in Expectation Propagation Jonathan So Richard E. Turner 30 0 0 03 Jun 2024
BlackJAX: Composable Bayesian inference in JAX Alberto Cabezas Adrien Corenflos Junpeng Lao Rémi Louf Antoine Carnec ... Kevin P. Murphy Juan Camilo Orduz Karm Patel Xi Wang Robert Zinkov DRL MLAU 30 18 0 16 Feb 2024
Improving Hyperparameter Learning under Approximate Inference in Gaussian Process Models Rui Li S. T. John Arno Solin BDL 15 3 0 07 Jun 2023
Variational Gaussian Process Diffusion Processes Prakhar Verma Vincent Adam Arno Solin DiffM 14 4 0 03 Jun 2023
Efficient Sensor Placement from Regression with Sparse Gaussian Processes in Continuous and Discrete Spaces Kalvik Jakkala Srinivas Akella 13 1 0 28 Feb 2023
Short-term Prediction and Filtering of Solar Power Using State-Space Gaussian Processes Sean Nassimiha Peter Dudfield Jack Kelly M. Deisenroth So Takao 16 1 0 01 Feb 2023
Markovian Gaussian Process Variational Autoencoders Harrison Zhu Carles Balsells Rodas Yingzhen Li BDL AI4TS 27 14 0 12 Jul 2022
A Look at Improving Robustness in Visual-inertial SLAM by Moment Matching Arno Solin Ruixiao Li Andrea Pilzer 8 1 0 27 May 2022
Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam Mohammad Emtiyaz Khan Didrik Nielsen Voot Tangkaratt Wu Lin Y. Gal Akash Srivastava ODL 74 266 0 13 Jun 2018