RESEARCH PAPER · Patterns · 2023
Optimal decision-making in high-throughput virtual screening pipelines
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Optimal high-throughput virtual screening pipeline for efficient selection of redox-active organic materials
iScience · 2022-12-06
Hyun-Myung Woo, Omar Adel Allam, Junhe Chen, Seung Soon Jang, Byung-Jun Yoon
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Computer Graphics Forum · 2023-06-01
Bharat Kale, Austin Clyde, Maoyuan Sun, Arvind Ramanathan, Rick L. Stevens, Michael E. Papka
Read original paper ↗ ·Multi-objective latent space optimization of generative molecular design models
Patterns · 2024-08-12
A N M Nafiz Abeer, Nathan M. Urban, M. Ryan Weil, Francis J. Alexander, Byung-Jun Yoon
Read original paper ↗ ·Employing artificial intelligence to steer exascale workflows with colmena
The International Journal of High Performance Computing Applications · 2024-10-08
Logan T. Ward, J. Gregory Pauloski, Valérie Hayot‐Sasson, Yadu Babuji, Alexander Brace, Ryan Chard, Kyle Chard, Rajeev Thakur, Ian T Foster
Read original paper ↗ ·An Effective Pipeline for Training Variational Autoencoders for Synthesizable and Optimized Molecular Design
IEEE Access · 2024-12-27
Fardeen H. Mozumder, Byung-Jun Yoon
Read original paper ↗ ·Multi-Fidelity Learning in High-Throughput Materials Screening: A Review of Surrogate Strategies and Their Broken Promises
Journal of Computational and Data-Driven Materials Engineering · 2025-01-01
Anna Svensson, Erik Lindberg
Read original paper ↗ ·Enhancing generative molecular design via uncertainty-guided fine-tuning of variational autoencoders
Molecular Systems Design & Engineering · 2025-10-17
A N M Nafiz Abeer, Sanket R. Jantre, Nathan M. Urban, Byung-Jun Yoon
Read original paper ↗ ·Bioinspired material design for oral targeted delivery Systems: From structural bioinspiration to functional implementation
Biochemical Pharmacology · 2026-01-27
Minhui Xu, Tao Sun, Huangbang Liang, Guangfu Feng, Qiongfang Hu, Yuanchun Du, Jun Fang
Read original paper ↗ ·Recent advances, challenges and future perspectives of polycyclic aromatic hydrocarbons as materials for metal-ion batteries – A comprehensive review
Progress in Materials Science · 2026-03-27
Ilya V. Chepkasov, Stanislav A. Evlashin, Alexander G. Kvashnin
Read original paper ↗ ·Closed-Loop Machine Learning in Materials Discovery: From Predict-Validate-Update Paradigms to Autonomous Ecosystems
Archives of Computational Methods in Engineering · 2026-07-13
Yunseok Kim, Sua Kim, Hwanyeol Park
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