Mark van der Wilk
39 papers · 2014–2026 · 7 venues · across top CS/AI venues
This profile combines several different researchers. Authors are keyed by name, and this name's papers fall into 10 separate collaboration groups - the largest holds only 38% of them. Pick the group below that matches the researcher you mean. How a shared name is split.
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Which Mark van der Wilk?
4 groups of papers that share co-authors internally but none with each other - each most likely a different researcher. Pick one to see its papers.
with Adrià Garriga-Alonso, Sebastian W. Ober, Vincent Fortuin
11 papers
· 2021–2024
· NeurIPS, UAI, ICML
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Learning in Deep Factor Graphs with Gaussian Belief Propagation
ICML 2024
Noether's Razor: Learning Conserved Quantities
NeurIPS 2024
Learning Layer-wise Equivariances Automatically using Gradients
NeurIPS 2023
Stochastic Marginal Likelihood Gradients using Neural Tangent Kernels
ICML 2023
Bayesian Neural Network Priors Revisited
ICLR 2022
Data augmentation in Bayesian neural networks and the cold posterior effect
UAI 2022
Invariance Learning in Deep Neural Networks with Differentiable Laplace Approximations
NeurIPS 2022
Last Layer Marginal Likelihood for Invariance Learning
AISTATS 2022
Relaxing Equivariance Constraints with Non-stationary Continuous Filters
NeurIPS 2022
Correlated weights in infinite limits of deep convolutional neural networks
UAI 2021
The promises and pitfalls of deep kernel learning
UAI 2021
6 papers whose co-authors appear nowhere else under this name
Adjusting Model Size in Continual Gaussian Processes: How Big is Big Enough?
ICML 2025
Rethinking Aleatoric and Epistemic Uncertainty
ICML 2025
Actually Sparse Variational Gaussian Processes
AISTATS 2023
Learning invariant weights in neural networks
UAI 2022
Bayesian Layers: A Module for Neural Network Uncertainty
NeurIPS 2019
Scalable Bayesian dynamic covariance modeling with variational Wishart and inverse Wishart processes
NeurIPS 2019