AI-Assisted Discovery of Quantitative and Formal Models in Social Science. - Julia Balla; Sihao Huang; Owen Dugan; Rumen Dangovski; Marin Soljacic (CoRR, 2022)

Q-Flow: Generative Modeling for Differential Equations of Open Quantum Dynamics with Normalizing Flows. - Owen M. Dugan; Peter Y. Lu; Rumen Dangovski; Di Luo; Marin Soljacic (ICML, 2023)

QuanTA: Efficient High-Rank Fine-Tuning of LLMs with Quantum-Informed Tensor Adaptation. - Zhuo Chen; Rumen Dangovski; Charlotte Loh; Owen Dugan; Di Luo; Marin Soljacic (NeurIPS, 2024)

OccamLLM: Fast and Exact Language Model Arithmetic in a Single Step. - Owen Dugan; Donato Jiménez-Benetó; Charlotte Loh; Zhuo Chen; Rumen Dangovski; Marin Soljacic (NeurIPS, 2024)

Towards Learning High-Precision Least Squares Algorithms with Sequence Models. - Jerry Weihong Liu; Jessica Grogan; Owen M. Dugan; Ashish Rao; Simran Arora; Atri Rudra; Christopher Ré (ICLR, 2025)

Predicting band gap from chemical composition: A simple learned model for a material property with atypical statistics. - Andrew Ma; Owen Dugan; Marin Soljacic (CoRR, 2025)

Towards Learning High-Precision Least Squares Algorithms with Sequence Models. - Jerry Liu; Jessica Grogan; Owen Dugan; Ashish Rao; Simran Arora; Atri Rudra; Christopher Ré (CoRR, 2025)