Search Results for author:
Found 3 papers, 2 papers with code
Weak Form Generalized Hamiltonian Learning
We present a method for learning generalized Hamiltonian decompositions of ordinary differential equations given a set of noisy time series measurements.
Discretely Relaxing Continuous Variables for tractable Variational Inference
We explore a new research direction in Bayesian variational inference with discrete latent variable priors where we exploit Kronecker matrix algebra for efficient and exact computations of the evidence lower bound (ELBO).
Scalable Gaussian Processes with Grid-Structured Eigenfunctions (GP-GRIEF)
We introduce a kernel approximation strategy that enables computation of the Gaussian process log marginal likelihood and all hyperparameter derivatives in O(p) time.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
