Probing gas adsorption in MOFs using an efficient ab initio widom insertion Monte Carlo method. - Youhan Lee; Roberta Poloni; Jihan Kim (J. Comput. Chem., 2016)

A community-powered search of machine learning strategy space to find NMR property prediction models. - Lars A. Bratholm; Will Gerrard; Brandon M. Anderson; Shaojie Bai; Sunghwan Choi; Lam Dang; Pavel Hanchar; Addison Howard; Guillaume Huard; Sanghoon Kim; J. Zico Kolter; Risi Kondor; et al. (CoRR, 2020)

Reconstruction of Compton Edges in Plastic Gamma Spectra Using Deep Autoencoder. - Byoungil Jeon; Youhan Lee; Myungkook Moon; Jongyul Kim 003; Gyuseong Cho (Sensors, 2020)

Predictive models of RNA degradation through dual crowdsourcing. - Hannah K. Wayment-Steele; Wipapat Kladwang; Andrew M. Watkins; Do Soon Kim; Bojan Tunguz; Walter Reade; Maggie Demkin; Jonathan Romano; Roger Wellington-Oguri; John J. Nicol; Jiayang Gao; Kazuki Onodera; et al. (CoRR, 2021)

Efficient Multilingual Multi-modal Pre-training through Triple Contrastive Loss. - Youhan Lee; Kyungtae Lim; Woonhyuk Baek; Byungseok Roh; Saehoon Kim (COLING, 2022)

Deep learning models for predicting RNA degradation via dual crowdsourcing. - Hannah K. Wayment-Steele; Wipapat Kladwang; Andrew M. Watkins; Do Soon Kim; Bojan Tunguz; Walter Reade; Maggie Demkin; Jonathan Romano; Roger Wellington-Oguri; John J. Nicol; Jiayang Gao; Kazuki Onodera; et al. (Nat. Mac. Intell., 2022)

ProtFIM: Fill-in-Middle Protein Sequence Design via Protein Language Models. - Youhan Lee; Hasun Yu (CoRR, 2023)

Solvent: A Framework for Protein Folding. - Jaemyung Lee 004; Kyeongtak Han; Jaehoon Kim; Hasun Yu; Youhan Lee (CoRR, 2023)

BOK-VQA: Bilingual outside Knowledge-Based Visual Question Answering via Graph Representation Pretraining. - MinJun Kim; Seungwoo Song; Youhan Lee; Haneol Jang; Kyungtae Lim (AAAI, 2024)

Pre-training Sequence, Structure, and Surface Features for Comprehensive Protein Representation Learning. - Youhan Lee; Hasun Yu; Jaemyung Lee 004; Jaehoon Kim (ICLR, 2024)

BioNeMo Framework: a modular, high-performance library for AI model development in drug discovery. - Peter St. John; Dejun Lin; Polina Binder; Malcolm Greaves; Vega Shah; John St. John; Adrian Lange; Patrick D. Hsu; Rajesh Illango; Arvind Ramanathan; Anima Anandkumar; David H. Brookes; et al. (CoRR, 2024)