Mark van der Wilk

Associate Professor@University of Oxford·英国·OpenReview

研究方向

bayesian inference · variational inference · gaussian processes · dynamical systems · model-based reinforcement learning · reinforcement learning · uncertainty

7.8

Adjusting Model Size in Continual Gaussian Processes: How Big is Big Enough?

ICML 2025Spotlight

三作

6.8

Estimating Interventional Distributions with Uncertain Causal Graphs through Meta-Learning

合作者 (20)

Guiomar Pescador-Barrios

Freddie Bickford Smith

1 篇

Jannik Kossen

1 篇

Mark van der Wilk

Adjusting Model Size in Continual Gaussian Processes: How Big is Big Enough?

Estimating Interventional Distributions with Uncertain Causal Graphs through Meta-Learning

A Meta-Learning Approach to Bayesian Causal Discovery

Continuous Bayesian Model Selection for Multivariate Causal Discovery

Rethinking Aleatoric and Epistemic Uncertainty

Noether's Razor: Learning Conserved Quantities

Transition Constrained Bayesian Optimization via Markov Decision Processes