A PINN Approach to Symbolic Differential Operator Discovery with Sparse Data. - Lena Podina; Brydon Eastman; Mohammad Kohandel (CoRR, 2022)

Better Peer Grading through Bayesian Inference. - Hedayat Zarkoob; Greg d'Eon; Lena Podina; Kevin Leyton-Brown (AAAI, 2023)

Universal Physics-Informed Neural Networks: Symbolic Differential Operator Discovery with Sparse Data. - Lena Podina; Brydon Eastman; Mohammad Kohandel (ICML, 2023)

Denoising Diffusion Restoration Tackles Forward and Inverse Problems for the Laplace Operator. - Amartya Mukherjee; Melissa M. Stadt; Lena Podina; Mohammad Kohandel; Jun Liu 015 (CoRR, 2024)

Learning Chemotherapy Drug Action via Universal Physics-Informed Neural Networks. - Lena Podina; Ali Ghodsi 001; Mohammad Kohandel (CoRR, 2024)

Conformalized Physics-Informed Neural Networks. - Lena Podina; Mahdi Torabi Rad; Mohammad Kohandel (CoRR, 2024)

Enhancing Symbolic Regression and Universal Physics-Informed Neural Networks with Dimensional Analysis. - Lena Podina; Diba Darooneh; Joshveer Grewal; Mohammad Kohandel (CoRR, 2024)