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Navigating the Trade-Offs: A Quantitative Analysis of Reinforcement Learning Reward Functions for Autonomous Maritime Collision Avoidance2025 Journal of Marine Science and Engineering article Engineering Maritime Navigation and Safety Open access
Björn Krautwig, Dominik Wans, Li Li, Till Temmen, Lucas Koch, Markus Eisenbarth, +1 more
0citations -
Discovery of liquid crystalline polymers with high thermal conductivity using machine learning2025 npj Computational Materials article Materials Science Machine Learning in Materials Science Open access
Hayato Maeda, Stephen Wu, Rika Marui, Erina Yoshida, Kan Hatakeyama‐Sato, Yuta Nabae, +13 more
20citations -
Benchmarking short-range machine learning potentials for atomistic simulations of metal/electrolyte interfaces2026 arXiv (Cornell University) preprint Materials Science Machine Learning in Materials Science Open access
Lucas B. T. de Kam, Jiaxin Zhu, Ankit Mathanker, Katharina Doblhoff-Dier, Nitish Govindarajan
4citations -
Multi-objective optimization and quantum hybridization of equivariant deep learning interatomic potentials2026 Computational Materials Science article Materials Science Machine Learning in Materials Science Open access
G. Laskaris, D. Morozov, D. Tarpanov, A. Seth, J. Procelewska, Gopalakrishnan Sai Gautam, +3 more
2citations -
Few Shot Learning for the Classification of Confocal Laser Endomicroscopy Images of Head and Neck Tumors2023 arXiv (Cornell University) preprint Computer Science Domain Adaptation and Few-Shot Learning Open access
Marc Aubreville, Zhaoya Pan, Matti Sievert, Jonas Ammeling, Jonathan Ganz, Nicolai Oetter, +3 more
0citations