Austin Tripp - RankMe

24 papers A* 7Journal 17

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A Computational Community Blind Challenge on Pan-Coronavirus Drug Discovery Data. J. Chem. Inf. Model. Hugo MacDermott-Opeskin, Jenke Scheen, Cas Wognum, Joshua T. Horton, Devany West, Alexander Matthew Payne, Maria A. Castellanos, Sean Colby, Edward J. Griffen, David Cousins, Jessica Stacey, Lauren Reid, Jasmin Cara Aschenbrenner, Daren Fearon, Blake Balcomb, Peter Marples, Charles W. E. Tomlinson, Ryan Lithgo, Andre S. Godoy, Max Winokan, Haim Barr, Noa Lahav, Michael Lavi, Shirley Duberstein, Galit Cohen, Gwendolyn Fate, Bruce Lefker, Ralph Robinson, Tamas Szommer, Nick Lynch, David D. L. Minh, Van Ngoc Thuy La, Lulu Kang, Kate Huddleston, Ryan Renslow, Mallory Tollefson, W. Patrick Walters, Cynthia Xu, Jonny Hsu, Julien St-Laurent, Honore Etsmoberg, Lu Zhu, Andrew Quirke, Mohamed Iliyas Abdul Haleem, Irfan Alibay, Gunjan Baid, Benjamin Birnbaum, Kevin P. Bishop, Hugo-Javier Bohórquez, Ashmita Bose, C. J. Brown, Jackson W. Burns, Lianjin Cai, Ruel Cedeno, Stephane de Cesco, Vladimir I. Chupakhin, Finlay Clark, Daniel J. Cole, Carles Corbi-Verge, Muhammad Danial, Alec Davi, Wim Dehaen, Niklas Piet Doering, Alexis Dougha, Marie-Pierre Dréanic, Bryce Eakin, Anatol Ehrlich, Rokas Elijosius, Jozef Fülöp, Anthony Gitter, Kenneth Goossens, Yaowen Gu, Teresa Head-Gordon, Laurent Hoffer, Johan Hofmans, Ellena Jiang, Benjamin Kaminow, Sina Khosravi, Asma Feriel Khoualdi, Eelke B. Lenselink, Zhirong Liu, Yue Liu, Sijie Liu, Yizhou Ma, Patrick Maher, Imke Mayer, Oscar Mendez-Lucio, Antonia S. J. S. Mey, Julien Michel, Floriane Montanari, Taoyu Niu, Ryusei Ogino, Ashok Palaniappan, Xiaolin Pan, Auro Patnaik, Long-Hung Dinh Pham, Luis Pinto, Justin Purnomo, Alex Rich, Lars L. Schaaf, Christoph Schran, Rajeev Kumar Singh, Mounika Srilakshmi, Satya Pratik Srivastava, Kunyang Sun, Zhaoxi Sun, Valerij Talagayev, Balamurugan Thirukonda Subramanian Balakrishnan, Ida Titus, Alexandre Tkatchenko, Wojtek Treyde, Giovanni Tricarico, Austin Tripp, Nopsinth Vithayapalert, Yingze Wang, Azmine Toushik Wasi, Steffen Wedig, Gerhard Wolber, Bofei Xu, Weijun Zhou, Frank von Delft, Alpha Lee, Karla Kirkegaard, Peter Sjö, James S. Fraser, John D. Chodera
2025	J	`jnl`	Batched Bayesian Optimization by Maximizing the Probability of Including the Optimum. J. Chem. Inf. Model. Jenna C. Fromer, Runzhong Wang, Mrunali Manjrekar, Austin Tripp, José Miguel Hernández-Lobato, Connor W. Coley
2025	J	`jnl`	Bayesian Optimization for Molecules Should Be Pareto-Aware. CoRR Anabel Yong, Austin Tripp, Layla Hosseini-Gerami, Brooks Paige
2025	J	`jnl`	Hash Collisions in Molecular Fingerprints: Effects on Property Prediction and Bayesian Optimization. CoRR Walter Virany, Austin Tripp
2024	J	`jnl`	A Deep Generative Model for the Design of Synthesizable Ionizable Lipids. CoRR Yuxuan Ou, Jingyi Zhao, Austin Tripp, Morteza Rasoulianboroujeni, José Miguel Hernández-Lobato
2024	J	`jnl`	Batched Bayesian optimization with correlated candidate uncertainties. CoRR Jenna C. Fromer, Runzhong Wang, Mrunali Manjrekar, Austin Tripp, José Miguel Hernández-Lobato, Connor W. Coley
2024	J	`jnl`	Diagnosing and fixing common problems in Bayesian optimization for molecule design. CoRR Austin Tripp, José Miguel Hernández-Lobato
2024	J	`jnl`	Generative Model for Synthesizing Ionizable Lipids: A Monte Carlo Tree Search Approach. CoRR Jingyi Zhao, Yuxuan Ou, Austin Tripp, Morteza Rasoulianboroujeni, José Miguel Hernández-Lobato
2024	A*	`conf`	Retro-fallback: retrosynthetic planning in an uncertain world. ICLR Austin Tripp, Krzysztof Maziarz, Sarah Lewis, Marwin H. S. Segler, José Miguel Hernández-Lobato
2024	A*	`conf`	Stochastic Gradient Descent for Gaussian Processes Done Right. ICLR Jihao Andreas Lin, Shreyas Padhy, Javier Antorán, Austin Tripp, Alexander Terenin, Csaba Szepesvári, José Miguel Hernández-Lobato, David Janz
2023	A*	`conf`	GAUCHE: A Library for Gaussian Processes in Chemistry. NeurIPS Ryan-Rhys Griffiths, Leo Klarner, Henry B. Moss, Aditya Ravuri, Sang Truong, Yuanqi Du, Samuel Stanton, Gary Tom, Bojana Rankovic, Arian Rokkum 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 A. Lee, Bingqing Cheng, Alán Aspuru-Guzik, Philippe Schwaller, Jian Tang
2023	J	`jnl`	Genetic algorithms are strong baselines for molecule generation. CoRR Austin Tripp, José Miguel Hernández-Lobato
2023	A*	`conf`	Meta-learning Adaptive Deep Kernel Gaussian Processes for Molecular Property Prediction. ICLR Wenlin Chen, Austin Tripp, José Miguel Hernández-Lobato
2023	J	`jnl`	Re-evaluating Retrosynthesis Algorithms with Syntheseus. CoRR Krzysztof Maziarz, Austin Tripp, Guoqing Liu, Megan Stanley, Shufang Xie, Piotr Gainski, Philipp Seidl, Marwin H. S. Segler
2023	J	`jnl`	Retro-fallback: retrosynthetic planning in an uncertain world. CoRR Austin Tripp, Krzysztof Maziarz, Sarah Lewis, Marwin H. S. Segler, José Miguel Hernández-Lobato
2023	A*	`conf`	Retrosynthetic Planning with Dual Value Networks. ICML Guoqing Liu, Di Xue, Shufang Xie, Yingce Xia, Austin Tripp, Krzysztof Maziarz, Marwin H. S. Segler, Tao Qin, Zongzhang Zhang, Tie-Yan Liu
2023	J	`jnl`	Retrosynthetic Planning with Dual Value Networks. CoRR Guoqing Liu, Di Xue, Shufang Xie, Yingce Xia, Austin Tripp, Krzysztof Maziarz, Marwin H. S. Segler, Tao Qin, Zongzhang Zhang, Tie-Yan Liu
2023	J	`jnl`	Stochastic Gradient Descent for Gaussian Processes Done Right. CoRR Jihao Andreas Lin, Shreyas Padhy, Javier Antorán, Austin Tripp, Alexander Terenin, Csaba Szepesvári, José Miguel Hernández-Lobato, David Janz
2023	A*	`conf`	Tanimoto Random Features for Scalable Molecular Machine Learning. NeurIPS Austin Tripp, Sergio Bacallado, Sukriti Singh, José Miguel Hernández-Lobato
2023	J	`jnl`	Tanimoto Random Features for Scalable Molecular Machine Learning. CoRR Austin Tripp, Sergio Bacallado, Sukriti Singh, José Miguel Hernández-Lobato
2022	J	`jnl`	GAUCHE: A Library for Gaussian Processes in Chemistry. CoRR Ryan-Rhys Griffiths, Leo Klarner, Henry B. Moss, Aditya Ravuri, Sang Truong, Bojana Rankovic, Yuanqi Du, Arian R. Jamasb, Julius Schwartz, Austin Tripp, Gregory Kell, Anthony Bourached, Alex Chan, Jacob Moss, Chengzhi Guo, Alpha A. Lee, Philippe Schwaller, Jian Tang
2022	J	`jnl`	Meta-learning Adaptive Deep Kernel Gaussian Processes for Molecular Property Prediction. CoRR Wenlin Chen, Austin Tripp, José Miguel Hernández-Lobato
2020	A*	`conf`	Sample-Efficient Optimization in the Latent Space of Deep Generative Models via Weighted Retraining. NeurIPS Austin Tripp, Erik A. Daxberger, José Miguel Hernández-Lobato
2020	J	`jnl`	Sample-Efficient Optimization in the Latent Space of Deep Generative Models via Weighted Retraining. CoRR Austin Tripp, Erik A. Daxberger, José Miguel Hernández-Lobato