Tripp, Austin

18 publications

NeurIPSW 2024 A Deep Generative Model for the Design of Synthesizable Ionizable Lipids Yuxuan Ou, Jingyi Zhao, Austin Tripp, Morteza Rasoulianboroujeni, José Miguel Hernández-Lobato

ICMLW 2024 Diagnosing and Fixing Common Problems in Bayesian Optimization for Molecule Design Austin Tripp, José Miguel Hernández-Lobato

NeurIPSW 2024 Generative Model for Synthesizing Ionizable Lipids: A Monte Carlo Tree Search Approach Jingyi Zhao, Yuxuan Ou, Austin Tripp, Morteza Rasoulianboroujeni, José Miguel Hernández-Lobato

ICLRW 2024 Re-Evaluating Retrosynthesis Algorithms with Syntheseus Krzysztof Maziarz, Austin Tripp, Guoqing Liu, Megan Stanley, Shufang Xie, Piotr Gaiński, Philipp Seidl, Marwin Segler

ICLR 2024 Retro-Fallback: Retrosynthetic Planning in an Uncertain World Austin Tripp, Krzysztof Maziarz, Sarah Lewis, Marwin Segler, José Miguel Hernández-Lobato

ICLR 2024 Stochastic Gradient Descent for Gaussian Processes Done Right Jihao Andreas Lin, Shreyas Padhy, Javier Antoran, Austin Tripp, Alexander Terenin, Csaba Szepesvari, José Miguel Hernández-Lobato, David Janz

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

ICLR 2023 Meta-Learning Adaptive Deep Kernel Gaussian Processes for Molecular Property Prediction Wenlin Chen, Austin Tripp, José Miguel Hernández-Lobato

NeurIPSW 2023 Re-Evaluating Retrosynthesis Algorithms with Syntheseus Krzysztof Maziarz, Austin Tripp, Guoqing Liu, Megan Stanley, Shufang Xie, Piotr Gaiński, Philipp Seidl, Marwin Segler

NeurIPSW 2023 Retro-Fallback: Retrosynthetic Planning in an Uncertain World Austin Tripp, Krzysztof Maziarz, Sarah Lewis, Marwin Segler, José Miguel Hernández-Lobato

ICML 2023 Retrosynthetic Planning with Dual Value Networks Guoqing Liu, Di Xue, Shufang Xie, Yingce Xia, Austin Tripp, Krzysztof Maziarz, Marwin Segler, Tao Qin, Zongzhang Zhang, Tie-Yan Liu

NeurIPS 2023 Tanimoto Random Features for Scalable Molecular Machine Learning Austin Tripp, Sergio Bacallado, Sukriti Singh, José Miguel Hernández-Lobato

ICLRW 2022 An Evaluation Framework for the Objective Functions of De Novo Drug Design Benchmarks Austin Tripp, Wenlin Chen, José Miguel Hernández-Lobato

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

NeurIPSW 2022 Meta-Learning Adaptive Deep Kernel Gaussian Processes for Molecular Property Prediction Wenlin Chen, Austin Tripp, José Miguel Hernández-Lobato

NeurIPSW 2022 Re-Evaluating Chemical Synthesis Planning Algorithms Austin Tripp, Krzysztof Maziarz, Sarah Lewis, Guoqing Liu, Marwin Segler

NeurIPSW 2021 A Fresh Look at De Novo Molecular Design Benchmarks Austin Tripp, Gregor N. C. Simm, José Miguel Hernández-Lobato

NeurIPS 2020 Sample-Efficient Optimization in the Latent Space of Deep Generative Models via Weighted Retraining Austin Tripp, Erik Daxberger, José Miguel Hernández-Lobato