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Accelerating high-throughput virtual screening through molecular
  pool-based active learning

Accelerating high-throughput virtual screening through molecular pool-based active learning

Chemical Science (Chem. Sci.), 2020
13 December 2020
David E. Graff
E. Shakhnovich
Connor W. Coley
ArXiv (abs)PDFHTML

Papers citing "Accelerating high-throughput virtual screening through molecular pool-based active learning"

48 / 48 papers shown
Structure-Aware Fusion with Progressive Injection for Multimodal Molecular Representation Learning
Structure-Aware Fusion with Progressive Injection for Multimodal Molecular Representation Learning
Zihao Jing
Yan Sun
Yan Yi Li
Sugitha Janarthanan
Alana Deng
Pingzhao Hu
145
2
0
24 Oct 2025
Fine-tuning LLMs with variational Bayesian last layer for high-dimensional Bayesian optimization
Fine-tuning LLMs with variational Bayesian last layer for high-dimensional Bayesian optimization
Haotian Xiang
Jinwen Xu
Qin Lu
288
2
0
01 Oct 2025
Steering an Active Learning Workflow Towards Novel Materials Discovery via Queue Prioritization
Steering an Active Learning Workflow Towards Novel Materials Discovery via Queue Prioritization
Marcus Schwarting
Logan T. Ward
Nathaniel Hudson
Xiaoli Yan
Ben Blaiszik
Santanu Chaudhuri
Eliu A. Huerta
Ian Foster
AI4CE
102
1
0
29 Sep 2025
Addressing the Cold-Start Problem for Personalized Combination Drug Screening
Addressing the Cold-Start Problem for Personalized Combination Drug Screening
Antoine de Mathelin
Christopher Tosh
Wesley Tansey
126
0
0
09 Sep 2025
Active Learning on Synthons for Molecular Design
Active Learning on Synthons for Molecular Design
Tom George Grigg
Mason Burlage
Oliver Brook Scott
Adam Taouil
Dominique Sydow
Liam Wilbraham
173
2
0
19 May 2025
El Agente: An Autonomous Agent for Quantum Chemistry
El Agente: An Autonomous Agent for Quantum Chemistry
Yunheng Zou
Austin H. Cheng
Abdulrahman Aldossary
Jiaru Bai
Shi Xuan Leong
...
Ilya Yakavets
Han Hao
Chris Crebolder
Varinia Bernales
Alán Aspuru-Guzik
362
1
0
05 May 2025
Large language models as uncertainty-calibrated optimizers for experimental discovery
Large language models as uncertainty-calibrated optimizers for experimental discovery
Bojana Ranković
Ryan-Rhys Griffiths
P. Schwaller
BDL
1.1K
3
0
08 Apr 2025
Preferential Multi-Objective Bayesian Optimization for Drug Discovery
Preferential Multi-Objective Bayesian Optimization for Drug Discovery
Tai Dang
Long-Hung Pham
Sang T. Truong
Ari Glenn
Wendy Nguyen
Edward A. Pham
Jeffrey S. Glenn
Sanmi Koyejo
Thang Luong
294
4
0
21 Mar 2025
Efficient Biological Data Acquisition through Inference Set Design
Efficient Biological Data Acquisition through Inference Set DesignInternational Conference on Learning Representations (ICLR), 2024
Ihor Neporozhnii
Julien Roy
Emmanuel Bengio
Jason Hartford
408
2
0
25 Oct 2024
Ranking over Regression for Bayesian Optimization and Molecule Selection
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
242
6
0
11 Oct 2024
Generative Flows on Synthetic Pathway for Drug Design
Generative Flows on Synthetic Pathway for Drug DesignInternational Conference on Learning Representations (ICLR), 2024
Seonghwan Seo
Minsu Kim
Tony Shen
Martin Ester
Jinkyoo Park
Sungsoo Ahn
Woo Youn Kim
367
19
0
06 Oct 2024
Closed-Form Test Functions for Biophysical Sequence Optimization
  Algorithms
Closed-Form Test Functions for Biophysical Sequence Optimization Algorithms
Samuel Stanton
R. Alberstein
Nathan C. Frey
Andrew Watkins
Kyunghyun Cho
417
7
0
28 Jun 2024
Efficient Evolutionary Search Over Chemical Space with Large Language Models
Efficient Evolutionary Search Over Chemical Space with Large Language Models
Haorui Wang
Marta Skreta
C. Ser
Wenhao Gao
Lingkai Kong
...
Yanqiao Zhu
Yuanqi Du
Alán Aspuru-Guzik
Kirill Neklyudov
Chao Zhang
372
43
0
23 Jun 2024
AI-coupled HPC Workflow Applications, Middleware and Performance
AI-coupled HPC Workflow Applications, Middleware and Performance
Wes Brewer
Ana Gainaru
Frédéric Suter
Feiyi Wang
M. Emani
S. Jha
401
28
0
20 Jun 2024
Understanding active learning of molecular docking and its applications
Understanding active learning of molecular docking and its applications
Jeonghyeon Kim
Juno Nam
Seongok Ryu
212
0
0
14 Jun 2024
Scoreformer: A Surrogate Model For Large-Scale Prediction of Docking
  Scores
Scoreformer: A Surrogate Model For Large-Scale Prediction of Docking Scores
Álvaro Ciudad
Adrián Morales-Pastor
Laura Malo
Isaac Filella-Merce
Víctor Guallar
Alexis Molina
307
2
0
13 Jun 2024
How Useful is Intermittent, Asynchronous Expert Feedback for Bayesian
  Optimization?
How Useful is Intermittent, Asynchronous Expert Feedback for Bayesian Optimization?
Agustinus Kristiadi
Felix Strieth-Kalthoff
Sriram Ganapathi Subramanian
Vincent Fortuin
Pascal Poupart
Geoff Pleiss
216
3
0
10 Jun 2024
Structure-based Drug Design Benchmark: Do 3D Methods Really Dominate?
Structure-based Drug Design Benchmark: Do 3D Methods Really Dominate?
Kangyu Zheng
Yingzhou Lu
Zaixi Zhang
Zhongwei Wan
Yao Ma
Marinka Zitnik
Tianfan Fu
ELM
236
11
0
04 Jun 2024
Generative Active Learning for the Search of Small-molecule Protein
  Binders
Generative Active Learning for the Search of Small-molecule Protein Binders
Maksym Korablyov
Cheng-Hao Liu
Moksh Jain
A. V. D. Sloot
Eric Jolicoeur
...
Marwin H. S. Segler
Michael M. Bronstein
A. Marinier
Mike Tyers
Yoshua Bengio
236
9
0
02 May 2024
Uplift Modeling Under Limited Supervision
Uplift Modeling Under Limited Supervision
G. Panagopoulos
Daniele Malitesta
Fragkiskos D. Malliaros
Jun Pang
CML
426
3
0
28 Mar 2024
A Sober Look at LLMs for Material Discovery: Are They Actually Good for
  Bayesian Optimization Over Molecules?
A Sober Look at LLMs for Material Discovery: Are They Actually Good for Bayesian Optimization Over Molecules?
Agustinus Kristiadi
Felix Strieth-Kalthoff
Marta Skreta
Pascal Poupart
Alán Aspuru-Guzik
Geoff Pleiss
429
51
0
07 Feb 2024
Navigating the Maize: Cyclic and conditional computational graphs for
  molecular simulation
Navigating the Maize: Cyclic and conditional computational graphs for molecular simulationDigital Discovery (DD), 2024
Thomas Löhr
Michael Dodds
Lili Cao
Mikhail Kabeshov
Michele Assante
J. Janet
Marco Klähn
Ola Engkvist
99
0
0
22 Jan 2024
Beyond Regrets: Geometric Metrics for Bayesian Optimization
Beyond Regrets: Geometric Metrics for Bayesian Optimization
Jungtaek Kim
323
0
0
03 Jan 2024
Multimodal deep representation learning for quantum cross-platform
  verification
Multimodal deep representation learning for quantum cross-platform verificationPhysical Review Letters (PRL), 2023
Yan Qian
Yuxuan Du
Zhenliang He
Min-hsiu Hsieh
Dacheng Tao
241
18
0
07 Nov 2023
Pareto Optimization to Accelerate Multi-Objective Virtual Screening
Pareto Optimization to Accelerate Multi-Objective Virtual ScreeningDigital Discovery (DD), 2023
Jenna C. Fromer
David E. Graff
Connor W. Coley
284
19
0
16 Oct 2023
Molecular De Novo Design through Transformer-based Reinforcement
  Learning
Molecular De Novo Design through Transformer-based Reinforcement Learning
Pengcheng Xu
Tao Feng
Tianfan Fu
Siddhartha Laghuvarapu
Jimeng Sun
623
4
0
09 Oct 2023
De Novo Drug Design with Joint Transformers
De Novo Drug Design with Joint Transformers
Adam Izdebski
Ewelina Węglarz-Tomczak
Ewa Szczurek
Jakub M. Tomczak
ViT
508
3
0
03 Oct 2023
PharmacoNet: Accelerating Large-Scale Virtual Screening by Deep
  Pharmacophore Modeling
PharmacoNet: Accelerating Large-Scale Virtual Screening by Deep Pharmacophore ModelingChemical Science (Chem. Sci.), 2023
Seonghwan Seo
Woo Youn Kim
390
8
0
01 Oct 2023
Large-scale Pretraining Improves Sample Efficiency of Active Learning
  based Molecule Virtual Screening
Large-scale Pretraining Improves Sample Efficiency of Active Learning based Molecule Virtual Screening
Zhonglin Cao
Simone Sciabola
Ye Wang
248
2
0
20 Sep 2023
Will More Expressive Graph Neural Networks do Better on Generative
  Tasks?
Will More Expressive Graph Neural Networks do Better on Generative Tasks?LOG IN (LOG IN), 2023
Xian-Quan Zou
Xiangyu Zhao
Pietro Lio
Yiren Zhao
220
3
0
23 Aug 2023
Optimizing Drug Design by Merging Generative AI With Active Learning
  Frameworks
Optimizing Drug Design by Merging Generative AI With Active Learning Frameworks
Isaac Filella-Merce
Alexis Molina
Marek Orzechowski
Lucía Díaz
Yangnv Zhu
Julia Vilalta Mor
Laura Malo
Ajay Yekkirala
Soumya S. Ray
Víctor Guallar
AI4CE
150
9
0
04 May 2023
Calibration and generalizability of probabilistic models on low-data
  chemical datasets with DIONYSUS
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
268
26
0
03 Dec 2022
Reinforced Genetic Algorithm for Structure-based Drug Design
Reinforced Genetic Algorithm for Structure-based Drug DesignNeural Information Processing Systems (NeurIPS), 2022
Tianfan Fu
Wenhao Gao
Connor W. Coley
Jimeng Sun
236
67
0
28 Nov 2022
Recent Developments in Structure-Based Virtual Screening Approaches
Recent Developments in Structure-Based Virtual Screening Approaches
C. Gorgulla
140
0
0
06 Nov 2022
Discovering Many Diverse Solutions with Bayesian Optimization
Discovering Many Diverse Solutions with Bayesian OptimizationInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2022
Natalie Maus
Kaiwen Wu
David Eriksson
Jacob R. Gardner
592
35
0
20 Oct 2022
An efficient graph generative model for navigating ultra-large
  combinatorial synthesis libraries
An efficient graph generative model for navigating ultra-large combinatorial synthesis librariesNeural Information Processing Systems (NeurIPS), 2022
Aryan Pedawi
P. Gniewek
Chao-Ling Chang
Brandon M. Anderson
H. V. D. Bedem
234
9
0
19 Oct 2022
Accurate, reliable and interpretable solubility prediction of druglike
  molecules with attention pooling and Bayesian learning
Accurate, reliable and interpretable solubility prediction of druglike molecules with attention pooling and Bayesian learning
Seongok Ryu
Sumin Lee
203
6
0
29 Sep 2022
Efficient Chemical Space Exploration Using Active Learning Based on
  Marginalized Graph Kernel: an Application for Predicting the Thermodynamic
  Properties of Alkanes with Molecular Simulation
Efficient Chemical Space Exploration Using Active Learning Based on Marginalized Graph Kernel: an Application for Predicting the Thermodynamic Properties of Alkanes with Molecular Simulation
Yan Xiang
Yunhao Tang
Zheng Gong
Hongyi Liu
Liang Wu
Guang Lin
Huai Sun
AI4CE
103
0
0
01 Sep 2022
Self-focusing virtual screening with active design space pruning
Self-focusing virtual screening with active design space pruningJournal of Chemical Information and Modeling (JCIM), 2022
David E. Graff
Matteo Aldeghi
Joseph A. Morrone
K. E. Jordan
Edward O. Pyzer-Knapp
Connor W. Coley
217
28
0
03 May 2022
Bayesian optimization with known experimental and design constraints for
  chemistry applications
Bayesian optimization with known experimental and design constraints for chemistry applicationsDigital Discovery (DD), 2022
Riley J. Hickman
Matteo Aldeghi
Florian Hase
A. Aspuru‐Guzik
300
47
0
29 Mar 2022
Local Latent Space Bayesian Optimization over Structured Inputs
Local Latent Space Bayesian Optimization over Structured InputsNeural Information Processing Systems (NeurIPS), 2022
Natalie Maus
Haydn Thomas Jones
Juston Moore
Matt J. Kusner
John Bradshaw
Jacob R. Gardner
BDL
425
96
0
28 Jan 2022
Bringing Atomistic Deep Learning to Prime Time
Bringing Atomistic Deep Learning to Prime Time
Nathan C. Frey
S. Samsi
Bharath Ramsundar
Connor W. Coley
V. Gadepally
AI4CE
244
0
0
09 Dec 2021
A Review on Parallel Virtual Screening Softwares for High Performance
  Computers
A Review on Parallel Virtual Screening Softwares for High Performance Computers
N. A. Murugan
Artur Podobas
Davide Gadioli
Emanuele Vitali
G. Palermo
Stefano Markidis
156
43
0
30 Nov 2021
Docking-based Virtual Screening with Multi-Task Learning
Docking-based Virtual Screening with Multi-Task Learning
Zijing Liu
Xianbin Ye
Xiaomin Fang
Fan Wang
Hua Wu
Haifeng Wang
164
3
0
18 Nov 2021
DOCKSTRING: easy molecular docking yields better benchmarks for ligand
  design
DOCKSTRING: easy molecular docking yields better benchmarks for ligand designJournal of Chemical Information and Modeling (JCIM), 2021
Miguel García-Ortegón
G. Simm
Austin Tripp
José Miguel Hernández-Lobato
A. Bender
S. Bacallado
263
108
0
29 Oct 2021
Opportunities for Machine Learning to Accelerate Halide Perovskite
  Commercialization and Scale-Up
Opportunities for Machine Learning to Accelerate Halide Perovskite Commercialization and Scale-UpMatter (Matter), 2021
Rishi E. Kumar
A. Tiihonen
Shijing Sun
D. Fenning
Zhe Liu
Tonio Buonassisi
134
21
0
08 Oct 2021
Benchmarking the Performance of Bayesian Optimization across Multiple
  Experimental Materials Science Domains
Benchmarking the Performance of Bayesian Optimization across Multiple Experimental Materials Science Domainsnpj Computational Materials (npj Comput Mater), 2021
Qiaohao Liang
Aldair E. Gongora
Zekun Ren
A. Tiihonen
Zhe Liu
...
K. Hippalgaonkar
Benji Maruyama
Keith A. Brown
John W Fisher Iii
Tonio Buonassisi
162
176
0
23 May 2021
Therapeutics Data Commons: Machine Learning Datasets and Tasks for Drug
  Discovery and Development
Therapeutics Data Commons: Machine Learning Datasets and Tasks for Drug Discovery and Development
Kexin Huang
Tianfan Fu
Wenhao Gao
Yue Zhao
Yusuf Roohani
J. Leskovec
Connor W. Coley
Cao Xiao
Jimeng Sun
Marinka Zitnik
OODLM&MA
366
405
0
18 Feb 2021
1
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