Mark van der Wilk
Mark van der Wilk
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Variational Transductive Learning?
Meaningful Metrics for Probabilistic Predictions
Causal Discovery through Bayesian Model Selection
OccaMLab at NeurIPS: GPs, Equivariance, Causality
Invariance Learning in Deep Neural Networks with Differentiable Laplace Approximations
Memory Safe Computations with XLA Compiler
Recommendations for Baselines and Benchmarking Approximate Gaussian Processes
Relaxing Equivariance Constraints with Non-stationary Continuous Filters
SnAKe: Bayesian Optimization with Pathwise Exploration
Sparse Convolutions on Lie Groups
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