Self-Supervised Learning with Lie Symmetries for Partial Differential Equations. - Grégoire Mialon; Quentin Garrido; Hannah Lawrence; Danyal Rehman; Yann LeCun; Bobak T. Kiani (NeurIPS, 2023)

Physics-constrained neural differential equations for learning multi-ionic transport. - Danyal Rehman; John H. Lienhard (CoRR, 2023)

Attention-enhanced neural differential equations for physics-informed deep learning of ion transport. - Danyal Rehman; John H. Lienhard (CoRR, 2023)

FORT: Forward-Only Regression Training of Normalizing Flows. - Danyal Rehman; Oscar Davis; Jiarui Lu; Jian Tang 005; Michael M. Bronstein; Yoshua Bengio; Alexander Tong 001; Avishek Joey Bose (CoRR, 2025)