4.4k citations · 6.2k across the 79 of their papers we have counts for
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Bayesian Optimization with Dimension Scheduling: Application to Biological Systems
Doniyor Ulmasov, Caroline Baroukh, Benoit Chachuat +2
Bayesian Optimization (BO) is a data-efficient method for global black-box optimization of an expensive-to-evaluate fitness function. BO typically assumes that computation cost of…
Data-Efficient Learning of Feedback Policies from Image Pixels using Deep Dynamical Models
John-Alexander M. Assael, Niklas Wahlström, Thomas B. Schön +1
Data-efficient reinforcement learning (RL) in continuous state-action spaces using very high-dimensional observations remains a key challenge in developing fully autonomous systems…
Gaussian Processes for Data-Efficient Learning in Robotics and Control
Marc Peter Deisenroth, Dieter Fox, Carl Edward Rasmussen
Autonomous learning has been a promising direction in control and robotics for more than a decade since data-driven learning allows to reduce the amount of engineering knowledge, w…
Distributed Gaussian Processes
Marc Peter Deisenroth, Jun Wei Ng
To scale Gaussian processes (GPs) to large data sets we introduce the robust Bayesian Committee Machine (rBCM), a practical and scalable product-of-experts model for large-scale di…
From Pixels to Torques: Policy Learning with Deep Dynamical Models
Niklas Wahlström, Thomas B. Schön, Marc Peter Deisenroth
Data-efficient learning in continuous state-action spaces using very high-dimensional observations remains a key challenge in developing fully autonomous systems. In this paper, we…