308 citations · 980 across the 64 of their papers we have counts for
3 papers · 2 filters
Numerically Stable Sparse Gaussian Processes via Minimum Separation using Cover Trees
Alexander Terenin, David R. Burt, Artem Artemev +4
Gaussian processes are frequently deployed as part of larger machine learning and decision-making systems, for instance in geospatial modeling, Bayesian optimization, or in latent…
Learning Invariant Weights in Neural Networks
Tycho F. A. van der Ouderaa, Mark van der Wilk
Assumptions about invariances or symmetries in data can significantly increase the predictive power of statistical models. Many commonly used models in machine learning are constra…
Invariance Learning in Deep Neural Networks with Differentiable Laplace Approximations
Alexander Immer, Tycho F. A. van der Ouderaa, Gunnar Rätsch +2
Data augmentation is commonly applied to improve performance of deep learning by enforcing the knowledge that certain transformations on the input preserve the output. Currently, t…