6 citations · 6 across the 7 of their papers we have counts for
3 papers · 1 filter
Spherical Inducing Features for Orthogonally-Decoupled Gaussian Processes
Louis C. Tiao, Vincent Dutordoir, Victor Picheny
Despite their many desirable properties, Gaussian processes (GPs) are often compared unfavorably to deep neural networks (NNs) for lacking the ability to learn representations. Rec…
Inducing Point Allocation for Sparse Gaussian Processes in High-Throughput Bayesian Optimisation
Henry B. Moss, Sebastian W. Ober, Victor Picheny
Sparse Gaussian Processes are a key component of high-throughput Bayesian Optimisation (BO) loops; however, we show that existing methods for allocating their inducing points sever…
Trieste: Efficiently Exploring The Depths of Black-box Functions with TensorFlow
Victor Picheny, Joel Berkeley, Henry B. Moss +13
We present Trieste, an open-source Python package for Bayesian optimization and active learning benefiting from the scalability and efficiency of TensorFlow. Our library enables th…