Scalable Bayesian Inference in Low-Dimensional Subspaces

Scalable Bayesian Inference in Low-Dimensional Subspaces

[BayesGroup Seminar]: Scalable Bayesian inference in low-dimensional subspacesПодробнее

[BayesGroup Seminar]: Scalable Bayesian inference in low-dimensional subspaces

Scalable Bayesian InferenceПодробнее

Scalable Bayesian Inference

Peng Chen - Projected Variational Methods for High-dimensional Bayesian InferenceПодробнее

Peng Chen - Projected Variational Methods for High-dimensional Bayesian Inference

10 May 2024 - Matias Altamirano Montero - Robust and Scalable Bayesian Inference (PhD seminar)Подробнее

10 May 2024 - Matias Altamirano Montero - Robust and Scalable Bayesian Inference (PhD seminar)

Scalable Modular Bayesian Inference with Normalizing FlowsПодробнее

Scalable Modular Bayesian Inference with Normalizing Flows

Dr. Peng Chen | Projected variational inference for high-dimensional Bayesian inverse problemsПодробнее

Dr. Peng Chen | Projected variational inference for high-dimensional Bayesian inverse problems

Scalable Bayesian Inference - NeurIPS 2018Подробнее

Scalable Bayesian Inference - NeurIPS 2018

Dr. Saifuddin Syed | Scalable Bayesian Inference with Annealing AlgorithmsПодробнее

Dr. Saifuddin Syed | Scalable Bayesian Inference with Annealing Algorithms

Jonathan Huggins: Coresets for Scalable Bayesian InferenceПодробнее

Jonathan Huggins: Coresets for Scalable Bayesian Inference

Scalable Bayesian Deep Learning with Modern Laplace ApproximationsПодробнее

Scalable Bayesian Deep Learning with Modern Laplace Approximations

Scaling Up Bayesian Inference for Big and Complex DataПодробнее

Scaling Up Bayesian Inference for Big and Complex Data

FoDA - L18 : Dimensionality Reduction : Low-Dimensional Subspaces & SVD (Chapter 7.1 - 7.2)Подробнее

FoDA - L18 : Dimensionality Reduction : Low-Dimensional Subspaces & SVD (Chapter 7.1 - 7.2)

Tamara Broderick: Automated Scalable Bayesian Inference via Data SummarizationПодробнее

Tamara Broderick: Automated Scalable Bayesian Inference via Data Summarization

Extending simulation-based Bayesian inference to higher dimensionsПодробнее

Extending simulation-based Bayesian inference to higher dimensions

Dan Foreman-Mackey - Methods for scalable probabilistic inference - IPAM at UCLAПодробнее

Dan Foreman-Mackey - Methods for scalable probabilistic inference - IPAM at UCLA

Olivier Zahm A Data Free Likelihood-Informed Subspace for Dim Reduction of Bayesian Inverse ProblemsПодробнее

Olivier Zahm A Data Free Likelihood-Informed Subspace for Dim Reduction of Bayesian Inverse Problems

Optimisation-based sampling approaches for hierarchical Bayesian inferenceПодробнее

Optimisation-based sampling approaches for hierarchical Bayesian inference

Evaluating Scalable Bayesian Deep Learning Methods for Robust Computer Vision | Qualitative ResultsПодробнее

Evaluating Scalable Bayesian Deep Learning Methods for Robust Computer Vision | Qualitative Results

Robert Bamler: Scalable Bayesian Inferece: New Tools for New ChallengesПодробнее

Robert Bamler: Scalable Bayesian Inferece: New Tools for New Challenges

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