Gaussian Process Molecule Property Prediction with FlowMO

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Gaussian Process Molecule Property Prediction with FlowMO

2 October 2020

Ryan-Rhys Griffiths

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Papers citing "Gaussian Process Molecule Property Prediction with FlowMO"

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Title
A decoupled alignment kernel for peptide membrane permeability predictions Ali Amirahmadi Gökçe Geylan Leonardo De Maria Farzaneh Etminani Mattias Ohlsson Alessandro Tibo 226 0 0 26 Nov 2025
Hash Collisions in Molecular Fingerprints: Effects on Property Prediction and Bayesian Optimization Walter Virany Austin Tripp 29 0 0 21 Nov 2025
Ranking over Regression for Bayesian Optimization and Molecule SelectionAPL Machine Learning (AML), 2024 Gary Tom Stanley Lo Samantha Corapi Alán Aspuru-Guzik Benjamín Sánchez-Lengeling BDL 155 5 0 11 Oct 2024
Be aware of overfitting by hyperparameter optimization! Igor V. Tetko R. V. Deursen Guillaume Godin AI4CE 214 24 0 30 Jul 2024
A Gaussian Process Model for Ordinal Data with Applications to Chemoinformatics Arron Gosnell Evangelos A. Evangelou 106 2 0 16 May 2024
Simulation Based Bayesian Optimization Roi Naveiro Becky Tang 219 1 0 19 Jan 2024
GFlowNets for AI-Driven Scientific DiscoveryDigital Discovery (DD), 2023 Moksh Jain T. Deleu Jason S. Hartford Cheng-Hao Liu Alex Hernandez-Garcia Yoshua Bengio AI4CE 264 74 0 01 Feb 2023
Inducing Point Allocation for Sparse Gaussian Processes in High-Throughput Bayesian OptimisationInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2023 Henry B. Moss Sebastian W. Ober Victor Picheny 304 33 0 24 Jan 2023
GAUCHE: A Library for Gaussian Processes in ChemistryNeural Information Processing Systems (NeurIPS), 2022 Ryan-Rhys Griffiths Leo Klarner Henry B. Moss Aditya Ravuri Sang T. Truong ... A. Lee Bingqing Cheng Alán Aspuru-Guzik P. Schwaller Jian Tang GP 323 54 0 06 Dec 2022
Calibration and generalizability of probabilistic models on low-data chemical datasets with DIONYSUSDigital Discovery (DD), 2022 Gary Tom Riley J. Hickman Aniket N. Zinzuwadia A. Mohajeri Benjamín Sánchez-Lengeling A. Aspuru‐Guzik 172 22 0 03 Dec 2022
Combining Latent Space and Structured Kernels for Bayesian Optimization over Combinatorial SpacesNeural Information Processing Systems (NeurIPS), 2021 Aryan Deshwal J. Doppa BDL 239 54 0 01 Nov 2021
High-Dimensional Bayesian Optimisation with Variational Autoencoders and Deep Metric Learning Antoine Grosnit Rasul Tutunov A. Maraval Ryan-Rhys Griffiths Alexander I. Cowen-Rivers ... Wenlong Lyu Zhitang Chen Jun Wang Jan Peters Haitham Bou-Ammar BDL DRL 208 71 0 07 Jun 2021
Assigning Confidence to Molecular Property PredictionExpert Opinion on Drug Discovery (EODD), 2021 AkshatKumar Nigam R. Pollice Matthew F. D. Hurley Riley J. Hickman Matteo Aldeghi Naruki Yoshikawa Seyone Chithrananda Vincent A. Voelz Alán Aspuru-Guzik AI4CE 223 50 0 23 Feb 2021
GIBBON: General-purpose Information-Based Bayesian OptimisatioNJournal of machine learning research (JMLR), 2021 Henry B. Moss David S. Leslie Javier I. González Paul Rayson 152 50 0 05 Feb 2021
Are we Forgetting about Compositional Optimisers in Bayesian Optimisation?Journal of machine learning research (JMLR), 2020 Antoine Grosnit Alexander I. Cowen-Rivers Rasul Tutunov Ryan-Rhys Griffiths Jun Wang Haitham Bou-Ammar 179 16 0 15 Dec 2020
Data-Driven Discovery of Molecular Photoswitches with Multioutput Gaussian Processes Ryan-Rhys Griffiths Jake L. Greenfield Aditya R. Thawani Arian R. Jamasb Henry B. Moss Anthony Bourached Penelope Jones William McCorkindale Alexander A. Aldrick Matthew J. Fuchter Alpha A. Lee 256 18 0 28 Jun 2020
Scalable Thompson Sampling using Sparse Gaussian Process Models Sattar Vakili Henry B. Moss A. Artemev Vincent Dutordoir Victor Picheny 364 35 0 09 Jun 2020
Achieving Robustness to Aleatoric Uncertainty with Heteroscedastic Bayesian Optimisation Ryan-Rhys Griffiths Alexander A. Aldrick Miguel García-Ortegón Vidhi R. Lalchand A. Lee 228 42 0 17 Oct 2019