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Athénaïs Honorine Gautier
Universität Bern
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Krikamol Muandet: Kernel Mean Embedding with Applications in Deconfounded Causal Learning
January 11 #1, 12 January 2022, 13 Views, 1:39:14
Carl Henrik Ek: Modulated Surrogates for Bayesian Optimisation
January 14 #3, 14 January 2022, 20 Views, 46:58
Mark van der Wilk: Approximations, Inductive Biases, and their Connections in Gaussian Processes
January 14 #1, 14 January 2022, 12 Views, 1:14:58
Dario Azzimonti: Skew Gaussian Processes for classification, preference and mixed problems
January 14 #2, 14 January 2022, 7 Views, 43:09
Andrew Gordon Wilson: How should we build scalable Gaussian processes?
January 13 #5, 13 January 2022, 17 Views, 1:11:06
José Miguel Hernández-Lobato: Molecule optimization with deep generative models
January 13 #4, 13 January 2022, 10 Views, 1:06:30
Johanna Ziegel: Kernel scores: A versatile class of proper scoring rules for evaluating probabilistic forecasts
January 13 #3, 13 January 2022, 28 Views, 43:01
George Wynne: A Spectral View of Kernel Stein Discrepancy: Unlocking Infinite Dimensions
January 13 #2, 13 January 2022, 17 Views, 42:32
Florence d'Alché-Buc: Learning to predict complex outputs: a kernel view
January 13 #1, 13 January 2022, 10 Views, 1:24:08
Soham Sarkar: Kernel methods: past, present, future
January 10 #3, 12 January 2022, 18 Views, 1:36:25
Dario Azzimonti & Cédric Travelletti: Sequential design of experiments with Gaussian Process models
January 10 #2, 12 January 2022, 12 Views, 1:32:45
Athénaïs Gautier & David Ginsbourger: Flexible, probabilistic function modelling with Gaussian Processes
January 10 #1, 12 January 2022, 39 Views, 1:34:57
Danica Sutherland: Better deep learning (sometimes) by learning kernel mean embeddings
January 12 #6, 12 January 2022, 20 Views, 46:50
Chris Oates: Robust Generalised Bayesian Inference for Intractable Likelihoods
January 12 #3, 12 January 2022, 28 Views, 45:43
Richard Wilkinson: Adjoint-aided inference of Gaussian process driven differential equations
January 12 #2, 12 January 2022, 20 Views, 44:51
Michael Gutmann: Accelerating Approximate Bayesian Computation with Kernels and Decision Making under Uncertainty
January 12 #1, 12 January 2022, 14 Views, 1:25:18
ST John: Gaussian processes for non-Gaussian likelihoods
January 10 #4, 12 January 2022, 36 Views, 1:22:45
Peter Frazier: Grey-Box Bayesian Optimization
January 11 #4, 12 January 2022, 17 Views, 1:19:50
Niklas Wahlström: Linearly and nonlinearly constrained Gaussian processes
January 11 #3, 12 January 2022, 22 Views, 45:23
Pierre-Cyril Aubin-Frankowski (INRIA Paris): Handling infinitely many inequality constraints in function optimization problems using kernel methods
Postdoc - 01, 10 January 2022, 29 Views, 5:01
Jean Carlo Guella (UNICAMP): Recent theoretical results on MMD, Energy distance, HSIC and its generalizations
Postdoc - 03, 10 January 2022, 33 Views, 4:48
Linda Chamakh (polytechnique): Explicit Mean-Embeddings for Financial Portfolio
Postdoc - 02, 10 January 2022, 33 Views, 4:50
Manuel Schürch (IDSIA/USI): Correlated Product of Experts for Sparse Gaussian Process Regression
Graduate Student - 06, 10 January 2022, 29 Views, 4:58
Ziang Niu (University of Pennsylvania): Discrepancy-based Inference for Intractable Generative Models using Quasi-Monte Carlo
Graduate Student - 05, 10 January 2022, 48 Views, 4:56
Iain Henderson (INSA Toulouse): Stochastic Processes Under Linear Differential Constraints : Application to Gaussian Process Regression for the 3 Dimensional Free Space Wave Equation
Graduate Student - 04, 10 January 2022, 43 Views, 5:27
Zachary A. Cosenza (University of California): Design of Cell Culture Media with Multi-Information Source Bayesian Optimization
Graduate Student - 03, 10 January 2022, 47 Views, 5:05
Luc Brogat-Motte (Télécom Paris): Reduced-rank Regression in Structured Prediction
Graduate Student - 02, 10 January 2022, 37 Views, 4:57
Raul Astudillo (Cornell University): Bayesian Optimization of Function Networks
Graduate Student - 01, 10 January 2022, 44 Views, 4:59