Gaussian Process Molecule Property Prediction with FlowMO

2 October 2020

Papers citing "Gaussian Process Molecule Property Prediction with FlowMO"

16 / 16 papers shown

Title
Ranking over Regression for Bayesian Optimization and Molecule Selection Gary Tom Stanley Lo Samantha Corapi Alán Aspuru-Guzik Benjamín Sánchez-Lengeling BDL 41 0 0 11 Oct 2024
Be aware of overfitting by hyperparameter optimization! Igor V. Tetko R. V. Deursen Guillaume Godin AI4CE 34 8 0 30 Jul 2024
A Gaussian Process Model for Ordinal Data with Applications to Chemoinformatics Arron Gosnell Evangelos A. Evangelou 27 0 0 16 May 2024
GFlowNets for AI-Driven Scientific Discovery Moksh Jain T. Deleu Jason S. Hartford Cheng-Hao Liu Alex Hernandez-Garcia Yoshua Bengio AI4CE 34 45 0 01 Feb 2023
Inducing Point Allocation for Sparse Gaussian Processes in High-Throughput Bayesian Optimisation Henry B. Moss Sebastian W. Ober Victor Picheny 32 24 0 24 Jan 2023
GAUCHE: A Library for Gaussian Processes in Chemistry 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 27 40 0 06 Dec 2022
Calibration and generalizability of probabilistic models on low-data chemical datasets with DIONYSUS Gary Tom Riley J. Hickman Aniket N. Zinzuwadia A. Mohajeri Benjamín Sánchez-Lengeling A. Aspuru‐Guzik 21 16 0 03 Dec 2022
Combining Latent Space and Structured Kernels for Bayesian Optimization over Combinatorial Spaces Aryan Deshwal J. Doppa BDL 32 42 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 22 59 0 07 Jun 2021
Assigning Confidence to Molecular Property Prediction AkshatKumar Nigam R. Pollice Matthew F. D. Hurley Riley J. Hickman Matteo Aldeghi Naruki Yoshikawa Seyone Chithrananda Vincent A. Voelz Alán Aspuru-Guzik AI4CE 18 46 0 23 Feb 2021
GIBBON: General-purpose Information-Based Bayesian OptimisatioN Henry B. Moss David S. Leslie Javier I. González Paul Rayson 21 43 0 05 Feb 2021
Are we Forgetting about Compositional Optimisers in Bayesian Optimisation? Antoine Grosnit Alexander I. Cowen-Rivers Rasul Tutunov Ryan-Rhys Griffiths Jun Wang Haitham Bou-Ammar 19 13 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 25 13 0 28 Jun 2020
Scalable Thompson Sampling using Sparse Gaussian Process Models Sattar Vakili Henry B. Moss A. Artemev Vincent Dutordoir Victor Picheny 8 34 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 31 35 0 17 Oct 2019
MoleculeNet: A Benchmark for Molecular Machine Learning Zhenqin Wu Bharath Ramsundar Evan N. Feinberg Joseph Gomes C. Geniesse Aneesh S. Pappu K. Leswing Vijay S. Pande OOD 184 1,778 0 02 Mar 2017