Position: Significant impact of numerical precision in scientific machine learning.
Y. Cho*, J. Yoo*, D.-J. Yi, S. Yang, S.M. Lee, M.S. Jeong, and J. Choo.
International Conference on Machine Learning (ICML) Position Track, 2026. Mat.Sci.

Robust and interpretable adaptation of equivariant materials foundation models via sparsity-promoting fine-tuning.
Y. Cho*, S. Yi*, W. Yang, S. Kang, Y.-W. Son, J. Choo, J. Lee, S.K. Kim, and H. Yoon.
International Conference on Learning Representations (ICLR), 2026. Mat.Sci.

Probing nanoscale structural perturbation in a WS2 monolayer via explainable artificial intelligence.
H.C. Suh*, J. Yoo*, K. Yeo, D.H. Kim, Y.S. Won, T. Kim, Y. Cho, K.K. Kim, S.M. Lee, H. Yang, D.-W. Kim, and M.S. Jeong.
Applied Physics Reviews, 2025. Mat.Sci.

Machine learning-based optical alignment simulation for K-DRIFT: off-axis freeform three mirror system.
S. Kim, Y. Kim, Y. Cho, J. Lee, S. Choi, J. Kim, K. Ahn, S.-H. Jeong, H. Cho, H. Choi, and J. Ko.
SPIE Astronomical Optics, 2025. Astronomy

Evaluating cell growth and hypoxic regions of 3D spheroids via a machine learning approach.
J. Yoo, J.W. Choi, E. Kim, E.-J. Park, A. Baek, J. Kim, M.S. Jeong, Y. Cho, T.G. Lee, and M.B. Heo.
Machine Learning: Science and Technology, 2024. Biology

Unraveling the role of Raman modes in evaluating the degree of reduction in graphene oxide via explainable artificial intelligence.
J. Yoo*, Y. Cho*, D.H. Kim, J. Kim, T.G. Lee, S.M. Lee, J. Choo, and M.S. Jeong.
Nano Today, 2024. Mat.Sci.

Towards Physically Reliable Molecular Representation Learning.
S. Yi, Y. Cho, J. Sul, S.W. Ko, S.K. Kim, J. Choo, H. Yoon, and J. Lee.
Conference on Uncertainty in Artificial Intelligence (UAI), 2023. Mat.Sci.

HistRED: A Historical Document-Level Relation Extraction Dataset.
S. Yang, M. Choi, Y. Cho, and J. Choo.
Annual Meeting of the Association for Computational Linguistics (ACL), 2023. NLP

Explainable Artificial Intelligence Approach to Identify the Origin of PhononAssisted Emission in WSe2 Monolayer.
J. Yoo*, Y. Cho*, B. Jeong, S.H. Choi, K.K. Kim, S.C. Lim, S.M. Lee, J. Choo, and M.S. Jeong.
Advanced Intelligent Systems, 2023. Mat.Sci.

Enemy Spotted: In-game Gun Sound Dataset for Gunshot Classification and Localization.
J. Park, Y. Cho, G. Sim, H. Lee, and J. Choo.
IEEE Conference on Games (CoG), 2022. Others

Progressive Upsampling Audio Synthesis via Efficient Adversarial Training.
Y. Cho*, M. Chang*, S. Lee, H. Lee, G.J. Kim, and J. Choo.
International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2021. Others

Knowledge Graph-based Question Answering with Electronic Health Records.
J. Park, Y. Cho, H. Lee, J. Choo, and E. Choi.
Machine Learning for Healthcare (MLHC), 2021. Others

Stego networks: Information Hiding in Deep Neural Networks.
Y. Cho*, B. Kim*, and J. Choo.
preprint, 2020. Others

A Framework for Developing Multi-perspective Prediction Models of Solar Energetic Particle Events.
S.-H. Park, S. Lee, Y. Cho, and S. Jang.
The 23rd Annual Meeting of the Asia Oceania Geosciences Society (AOGS), 2026. Astronomy

Hybrid Diffusions for Stable Molecular Structure Generation via Explicit Energy-based Model.
Y. Cho, S. Yi, S.K. Kim, H. Yoon, and J. Lee.
SynS & ML Workshop, ICML, 2023. Mat.Sci.

Deep-DFT: A Physics-ML Hybrid Approach to Predict Molecular Energy using Transformer.
Y. Cho*, H. Yoon*, S. Yi, J. Choo, M.J. Han, J. Lee, and S. Kim.
ML and the Physical Sciences Workshop, NeurIPS, 2021. Mat.Sci.

Physics-guided Reinforcement Learning for 3D Molecular Structures.
Y. Cho*, S. Kim*, P.P. Li, M.P. Surh, T.Y. Han, and J. Choo.
ML and the Physical Sciences Workshop, NeurIPS, 2019. Mat.Sci.