Christian Walder
Christian Walder
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Kernels and Gaussian Processes
All your loss are belong to Bayes
Quantile Propagation for Wasserstein-Approximate Gaussian Processes
Variational Inference for Sparse Gaussian Process Modulated Hawkes Process
Efficient non-parametric Bayesian Hawkes processes
New Tricks for Estimating Gradients of Expectations
Fast Bayesian Intensity Estimation for the Permanental Process
Diffeomorphic Dimensionality Reduction
Sparse Multiscale Gaussian Process Regression
Learning with Transformation Invariant Kernels
Implicit Surface Modelling with a Globally Regularised Basis of Compact Support
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