Ranking over Regression for Bayesian Optimization and Molecule Selection

Ranking over Regression for Bayesian Optimization and Molecule Selection

11 October 2024

Samantha Corapi

Alán Aspuru-Guzik

Benjamín Sánchez-Lengeling

Papers citing "Ranking over Regression for Bayesian Optimization and Molecule Selection"

15 / 15 papers shown

Title
Revisiting the Calibration of Modern Neural Networks Matthias Minderer Josip Djolonga Rob Romijnders F. Hubis Xiaohua Zhai N. Houlsby Dustin Tran Mario Lucic UQCV 96 365 0 15 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 91 47 0 23 Feb 2021
Top- $k$ Ranking Bayesian Optimization Q. Nguyen Sebastian Shenghong Tay Bryan Kian Hsiang Low Patrick Jaillet 70 22 0 19 Dec 2020
A benchmark study on reliable molecular supervised learning via Bayesian learning Doyeong Hwang Grace Lee Hanseok Jo Seyoul Yoon Seongok Ryu 56 9 0 12 Jun 2020
Differentiable Expected Hypervolume Improvement for Parallel Multi-Objective Bayesian Optimization Sam Daulton Maximilian Balandat E. Bakshy 44 241 0 09 Jun 2020
Uncertainty Quantification Using Neural Networks for Molecular Property Prediction Lior Hirschfeld Kyle Swanson Kevin Kaichuang Yang Regina Barzilay Connor W. Coley 72 191 0 20 May 2020
Open Graph Benchmark: Datasets for Machine Learning on Graphs Weihua Hu Matthias Fey Marinka Zitnik Yuxiao Dong Hongyu Ren Bowen Liu Michele Catasta J. Leskovec 298 2,725 0 02 May 2020
PyTorch: An Imperative Style, High-Performance Deep Learning Library Adam Paszke Sam Gross Francisco Massa Adam Lerer James Bradbury ... Sasank Chilamkurthy Benoit Steiner Lu Fang Junjie Bai Soumith Chintala ODL 439 42,393 0 03 Dec 2019
Analyzing Learned Molecular Representations for Property Prediction Kevin Kaichuang Yang Kyle Swanson Wengong Jin Connor W. Coley Philipp Eiden ... Andrew Palmer Volker Settels Tommi Jaakkola K. Jensen Regina Barzilay 98 1,315 0 02 Apr 2019
Fast Graph Representation Learning with PyTorch Geometric Matthias Fey J. E. Lenssen 3DH GNN 3DPC 220 4,336 0 06 Mar 2019
GuacaMol: Benchmarking Models for De Novo Molecular Design Nathan Brown Marco Fiscato Marwin H. S. Segler Alain C. Vaucher ELM 103 707 0 22 Nov 2018
Relational inductive biases, deep learning, and graph networks Peter W. Battaglia Jessica B. Hamrick V. Bapst Alvaro Sanchez-Gonzalez V. Zambaldi ... Pushmeet Kohli M. Botvinick Oriol Vinyals Yujia Li Razvan Pascanu AI4CE NAI 741 3,119 0 04 Jun 2018
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 328 1,826 0 02 Mar 2017
Automatic chemical design using a data-driven continuous representation of molecules Rafael Gómez-Bombarelli Jennifer N. Wei David Duvenaud José Miguel Hernández-Lobato Benjamín Sánchez-Lengeling Dennis Sheberla J. Aguilera-Iparraguirre Timothy D. Hirzel Ryan P. Adams Alán Aspuru-Guzik 3DV 149 2,927 0 07 Oct 2016
Practical Bayesian Optimization of Machine Learning Algorithms Jasper Snoek Hugo Larochelle Ryan P. Adams 349 7,934 0 13 Jun 2012