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

13 December 2020

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

43 / 43 papers shown

Title
GOLLuM: Gaussian Process Optimized LLMs -- Reframing LLM Finetuning through Bayesian Optimization Bojana Ranković P. Schwaller BDL 169 0 0 08 Apr 2025
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 69 0 0 21 Mar 2025
Efficient Biological Data Acquisition through Inference Set Design Ihor Neporozhnii Julien Roy Emmanuel Bengio Jason Hartford 48 0 0 25 Oct 2024
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
Batched Bayesian optimization by maximizing the probability of including the optimum Jenna C. Fromer Runzhong Wang Mrunali Manjrekar Austin Tripp José Miguel Hernández-Lobato Connor W. Coley 47 0 0 08 Oct 2024
Generative Flows on Synthetic Pathway for Drug Design Seonghwan Seo Minsu Kim Tony Shen Martin Ester Jinkyoo Park Sungsoo Ahn Woo Youn Kim 39 3 0 06 Oct 2024
Closed-Form Test Functions for Biophysical Sequence Optimization Algorithms Samuel Stanton R. Alberstein Nathan C. Frey Andrew Watkins Kyunghyun Cho 27 4 0 28 Jun 2024
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 47 12 0 23 Jun 2024
AI-coupled HPC Workflow Applications, Middleware and Performance Wes Brewer Ana Gainaru Frédéric Suter Feiyi Wang M. Emani S. Jha 30 10 0 20 Jun 2024
Understanding active learning of molecular docking and its applications Jeonghyeon Kim Juno Nam Seongok Ryu 35 0 0 14 Jun 2024
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 51 0 0 13 Jun 2024
How Useful is Intermittent, Asynchronous Expert Feedback for Bayesian Optimization? Agustinus Kristiadi Felix Strieth-Kalthoff Sriram Ganapathi Subramanian Vincent Fortuin Pascal Poupart Geoff Pleiss 44 2 0 10 Jun 2024
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 34 6 0 04 Jun 2024
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 21 4 0 02 May 2024
Uplift Modeling Under Limited Supervision G. Panagopoulos Daniele Malitesta Fragkiskos D. Malliaros Jun Pang CML 40 0 0 28 Mar 2024
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 30 21 0 07 Feb 2024
Navigating the Maize: Cyclic and conditional computational graphs for molecular simulation Thomas Löhr Michael Dodds Lili Cao Mikhail Kabeshov Michele Assante J. Janet Marco Klähn Ola Engkvist 16 0 0 22 Jan 2024
Beyond Regrets: Geometric Metrics for Bayesian Optimization Jungtaek Kim 29 0 0 03 Jan 2024
Multimodal deep representation learning for quantum cross-platform verification Yan Qian Yuxuan Du Zhenliang He Min-hsiu Hsieh Dacheng Tao 30 8 0 07 Nov 2023
Pareto Optimization to Accelerate Multi-Objective Virtual Screening Jenna C. Fromer David E. Graff Connor W. Coley 23 7 0 16 Oct 2023
Molecular De Novo Design through Transformer-based Reinforcement Learning Pengcheng Xu Tao Feng Tianfan Fu Siddhartha Laghuvarapu Jimeng Sun 14 1 0 09 Oct 2023
De Novo Drug Design with Joint Transformers Adam Izdebski Ewelina Węglarz-Tomczak Ewa Szczurek Jakub M. Tomczak ViT 21 3 0 03 Oct 2023
PharmacoNet: Accelerating Large-Scale Virtual Screening by Deep Pharmacophore Modeling Seonghwan Seo Woo Youn Kim 18 4 0 01 Oct 2023
Large-scale Pretraining Improves Sample Efficiency of Active Learning based Molecule Virtual Screening Zhonglin Cao Simone Sciabola Ye Wang 32 1 0 20 Sep 2023
Will More Expressive Graph Neural Networks do Better on Generative Tasks? Xian-Quan Zou Xiangyu Zhao Pietro Lio' Yiren Zhao 15 2 0 23 Aug 2023
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 14 5 0 04 May 2023
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
Reinforced Genetic Algorithm for Structure-based Drug Design Tianfan Fu Wenhao Gao Connor W. Coley Jimeng Sun 25 51 0 28 Nov 2022
Recent Developments in Structure-Based Virtual Screening Approaches C. Gorgulla 16 0 0 06 Nov 2022
Discovering Many Diverse Solutions with Bayesian Optimization N. Maus Kaiwen Wu David Eriksson J. Gardner 16 23 0 20 Oct 2022
An efficient graph generative model for navigating ultra-large combinatorial synthesis libraries Aryan Pedawi P. Gniewek Chao-Ling Chang Brandon M. Anderson H. V. D. Bedem 22 5 0 19 Oct 2022
Accurate, reliable and interpretable solubility prediction of druglike molecules with attention pooling and Bayesian learning Seongok Ryu Sumin Lee 16 5 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 Yan Xiang Yunhao Tang Zheng Gong Hongyi Liu Liang Wu Guang Lin Huai Sun AI4CE 20 0 0 01 Sep 2022
Self-focusing virtual screening with active design space pruning David E. Graff Matteo Aldeghi Joseph A. Morrone K. E. Jordan Edward O. Pyzer-Knapp Connor W. Coley 24 24 0 03 May 2022
Bayesian optimization with known experimental and design constraints for chemistry applications Riley J. Hickman Matteo Aldeghi Florian Hase A. Aspuru‐Guzik 13 21 0 29 Mar 2022
Local Latent Space Bayesian Optimization over Structured Inputs N. Maus Haydn Jones Juston Moore Matt J. Kusner John Bradshaw J. Gardner BDL 51 69 0 28 Jan 2022
Bringing Atomistic Deep Learning to Prime Time Nathan C. Frey S. Samsi Bharath Ramsundar Connor W. Coley V. Gadepally AI4CE 20 0 0 09 Dec 2021
A Review on Parallel Virtual Screening Softwares for High Performance Computers N. A. Murugan Artur Podobas Davide Gadioli Emanuele Vitali G. Palermo Stefano Markidis 19 32 0 30 Nov 2021
Docking-based Virtual Screening with Multi-Task Learning Zijing Liu Xianbin Ye Xiaomin Fang Fan Wang Hua-Hong Wu Haifeng Wang 14 2 0 18 Nov 2021
DOCKSTRING: easy molecular docking yields better benchmarks for ligand design Miguel García-Ortegón G. Simm Austin Tripp José Miguel Hernández-Lobato A. Bender S. Bacallado 37 75 0 29 Oct 2021
Opportunities for Machine Learning to Accelerate Halide Perovskite Commercialization and Scale-Up Rishi E. Kumar A. Tiihonen Shijing Sun D. Fenning Zhe Liu Tonio Buonassisi 17 10 0 08 Oct 2021
Benchmarking the Performance of Bayesian Optimization across Multiple Experimental Materials Science Domains Qiaohao Liang Aldair E. Gongora Zekun Ren A. Tiihonen Zhe Liu ... K. Hippalgaonkar Benji Maruyama Keith A. Brown John W Fisher Iii Tonio Buonassisi 29 118 0 23 May 2021
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 OOD LM&MA 30 261 0 18 Feb 2021