Dunn, Alexander

Unsupervised word embeddings capture latent knowledge from materials science literature

Tshitoyan, V., Dagdelen, J., Weston, L., Dunn, A., Rong, Z., Kononova, O., Persson, K. A., Ceder, G., & Jain, A. (2019) · Nature

Machine Learning in Materials ScienceTopic Modeling

Cited by 1,123

Structured information extraction from scientific text with large language models

Dagdelen, J., Dunn, A., Lee, S., Walker, N., Rosen, A. S., Ceder, G., Persson, K. A., & Jain, A. (2024) · Nature Communications

Topic ModelingMachine Learning in Materials Science

Cited by 771

Benchmarking materials property prediction methods: the Matbench test set and Automatminer reference algorithm

Dunn, A., Wang, Q., Ganose, A., Dopp, D., & Jain, A. (2020) · npj Computational Materials

Machine Learning in Materials ScienceAdvanced Chemical Physics Studies

Cited by 411

A critical examination of compound stability predictions from machine-learned formation energies

Bartel, C. J., Trewartha, A., Wang, Q., Dunn, A., Jain, A., & Ceder, G. (2020) · npj Computational Materials

Machine Learning in Materials ScienceAdvanced Chemical Physics Studies

Cited by 277

Structured information extraction from complex scientific text with fine-tuned large language models

Dunn, A., Dagdelen, J., Walker, N., Lee, S., Rosen, A. S., Ceder, G., Persson, K., & Jain, A. (2022) · arXiv

Topic ModelingMachine Learning in Materials Science

Cited by 67