Stanton, Samuel

9 publications

AISTATS 2023 Bayesian Optimization with Conformal Prediction Sets Samuel Stanton, Wesley Maddox, Andrew Gordon Wilson

NeurIPS 2023 GAUCHE: A Library for Gaussian Processes in Chemistry Ryan-Rhys Griffiths, Leo Klarner, Henry Moss, Aditya Ravuri, Sang Truong, Yuanqi Du, Samuel Stanton, Gary Tom, Bojana Rankovic, Arian Jamasb, Aryan Deshwal, Julius Schwartz, Austin Tripp, Gregory Kell, Simon Frieder, Anthony Bourached, Alex Chan, Jacob Moss, Chengzhi Guo, Johannes Peter Dürholt, Saudamini Chaurasia, Ji Won Park, Felix Strieth-Kalthoff, Alpha Lee, Bingqing Cheng, Alan Aspuru-Guzik, Philippe Schwaller, Jian Tang

NeurIPS 2023 Protein Design with Guided Discrete Diffusion Nate Gruver, Samuel Stanton, Nathan Frey, Tim G. J. Rudner, Isidro Hotzel, Julien Lafrance-Vanasse, Arvind Rajpal, Kyunghyun Cho, Andrew G Wilson

ICML 2022 Accelerating Bayesian Optimization for Biological Sequence Design with Denoising Autoencoders Samuel Stanton, Wesley Maddox, Nate Gruver, Phillip Maffettone, Emily Delaney, Peyton Greenside, Andrew Gordon Wilson

AISTATS 2021 Kernel Interpolation for Scalable Online Gaussian Processes Samuel Stanton, Wesley Maddox, Ian Delbridge, Andrew Gordon Wilson

NeurIPS 2021 Conditioning Sparse Variational Gaussian Processes for Online Decision-Making Wesley J Maddox, Samuel Stanton, Andrew G Wilson

NeurIPS 2021 Does Knowledge Distillation Really Work? Samuel Stanton, Pavel Izmailov, Polina Kirichenko, Alexander A Alemi, Andrew G Wilson

L4DC 2021 On the Model-Based Stochastic Value Gradient for Continuous Reinforcement Learning Brandon Amos, Samuel Stanton, Denis Yarats, Andrew Gordon Wilson

ICML 2020 Generalizing Convolutional Neural Networks for Equivariance to Lie Groups on Arbitrary Continuous Data Marc Finzi, Samuel Stanton, Pavel Izmailov, Andrew Gordon Wilson