2 citations · 2 across the 2 of their papers we have counts for
2 papers
cs.LG2022
Fantasizing with Dual GPs in Bayesian Optimization and Active Learning
Paul E. Chang, Prakhar Verma, ST John +3
Gaussian processes (GPs) are the main surrogate functions used for sequential modelling such as Bayesian Optimization and Active Learning. Their drawbacks are poor scaling with dat…
cs.LG2021★ 2 cited
Scalable Inference in SDEs by Direct Matching of the Fokker-Planck-Kolmogorov Equation
Arno Solin, Ella Tamir, Prakhar Verma
Simulation-based techniques such as variants of stochastic Runge-Kutta are the de facto approach for inference with stochastic differential equations (SDEs) in machine learning. Th…