Open Materials Generation with Stochastic Interpolants. - Höllmer, Philipp; Egg, Thomas; Martirossyan, Maya M.; Fuemmeler, Eric; Gupta, Amit; Shui, Zeren; Prakash, Pawan; Roitberg, Adrian; Liu, Mingjie; Karypis, George; Transtrum, Mark K.; Hennig, Richard G.; et al. (CoRR, 2025)

Fine-Tuning Language Models on Multiple Datasets for Citation Intention Classification. - Shui, Zeren; Karypis, Petros; Karls, Daniel S.; Wen, Mingjian; Manchanda, Saurav; Tadmor, Ellad B.; Karypis, George (2024)

Towards MatCore: A Unified Metadata Standard for Materials Science. - Greenberg, Jane; Bóveda-Aguirre, Pámela; Allison, John; Asinari, Pietro; Chan, Maria; Chandrasekaran, Anand; Ertekin, Elif; Garoufallou, Emmanouel; Galli, Giulia; Giannozzi, Paolo; Giustino, Feliciano; Goldbeck, Gerhard; et al. (2024)

Fine-Tuning Language Models on Multiple Datasets for Citation Intention Classification. - Shui, Zeren; Karypis, Petros; Karls, Daniel S.; Wen, Mingjian; Manchanda, Saurav; Tadmor, Ellad B.; Karypis, George (CoRR, 2024)

An information-matching approach to optimal experimental design and active learning. - Kurniawan, Yonatan; Neilsen, Tracianne B.; Francis, Benjamin L.; Stankovic, Alex M.; Wen, Mingjian; Nikiforov, Ilia A.; Tadmor, Ellad B.; Bulatov, Vasily V.; Lordi, Vincenzo; Transtrum, Mark K. (CoRR, 2024)

Active Planar Mass Distribution Estimation with Robotic Manipulation. - Yuan, Jiacheng; Choi, Changhyun; Tadmor, Ellad B.; Isler, Volkan (2023)

Active Mass Distribution Estimation from Tactile Feedback. - Yuan, Jiacheng; Choi, Changhyun; Tadmor, Ellad B.; Isler, Volkan (CoRR, 2023)

KLIFF: A framework to develop physics-based and machine learning interatomic potentials. - Wen, Mingjian; Afshar, Yaser; Elliott, Ryan S.; Tadmor, Ellad B. (Comput. Phys. Commun., 2022)

HPC Extensions to the OpenKIM Processing Pipeline. - Karls, Daniel S.; Clark, Steven M.; Waters, Brendon A.; Elliott, Ryan S.; Tadmor, Ellad B. (2022)

Extending OpenKIM with an Uncertainty Quantification Toolkit for Molecular Modeling. - Kurniawan, Yonatan; Petrie, Cody L.; Transtrum, Mark K.; Tadmor, Ellad B.; Elliott, Ryan S.; Karls, Daniel S.; Wen, Mingjian (2022)

Injecting Domain Knowledge from Empirical Interatomic Potentials to Neural Networks for Predicting Material Properties. - Shui, Zeren; Karls, Daniel S.; Wen, Mingjian; Nikiforov, Ilia A.; Tadmor, Ellad B.; Karypis, George (2022)

HPC Extensions to the OpenKIM Processing Pipeline. - Karls, Daniel S.; Clark, Steven M.; Waters, Brendon A.; Elliott, Ryan S.; Tadmor, Ellad B. (CoRR, 2022)

Injecting Domain Knowledge from Empirical Interatomic Potentials to Neural Networks for Predicting Material Properties. - Shui, Zeren; Karls, Daniel S.; Wen, Mingjian; Nikiforov, Ilia A.; Tadmor, Ellad B.; Karypis, George (CoRR, 2022)

Analysis of Rippling in Incommensurate One-Dimensional Coupled Chains. - Cazeaux, Paul; Luskin, Mitchell; Tadmor, Ellad B. (Multiscale Model. Simul., 2017)

Thermal parameter identification for non-Fourier heat transfer from molecular dynamics. - Singh, Amit; Tadmor, Ellad B. (J. Comput. Phys., 2015)

Efficient algorithms for discrete lattice calculations. - Arndt, Marcel; Sorkin, V.; Tadmor, Ellad B. (J. Comput. Phys., 2009)