Klarner, Leo

7 publications

ICML 2024 Context-Guided Diffusion for Out-of-Distribution Molecular and Protein Design Leo Klarner, Tim G. J. Rudner, Garrett M Morris, Charlotte Deane, Yee Whye Teh

TMLR 2023 Diffusion Models for Constrained Domains Nic Fishman, Leo Klarner, Valentin De Bortoli, Emile Mathieu, Michael John Hutchinson

ICML 2023 Drug Discovery Under Covariate Shift with Domain-Informed Prior Distributions over Functions Leo Klarner, Tim G. J. Rudner, Michael Reutlinger, Torsten Schindler, Garrett M Morris, Charlotte Deane, Yee Whye Teh

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 Metropolis Sampling for Constrained Diffusion Models Nic Fishman, Leo Klarner, Emile Mathieu, Michael Hutchinson, Valentin De Bortoli

ICMLW 2022 Bias in the Benchmark: Systematic Experimental Errors in Bioactivity Databases Confound Multi-Task and Meta-Learning Algorithms Leo Klarner, Michael Reutlinger, Torsten Schindler, Charlotte Deane, Garrett Morris

ICMLW 2022 GAUCHE: A Library for Gaussian Processes in Chemistry Ryan-Rhys Griffiths, Leo Klarner, Henry Moss, Aditya Ravuri, Sang T. Truong, Bojana Rankovic, Yuanqi Du, Arian Rokkum Jamasb, Julius Schwartz, Austin Tripp, Gregory Kell, Anthony Bourached, Alex Chan, Jacob Moss, Chengzhi Guo, Alpha Lee, Philippe Schwaller, Jian Tang