Molecular geometry prediction using a deep generative graph neural network. - Elman Mansimov; Omar Mahmood; Seokho Kang 001; Kyunghyun Cho (CoRR, 2019)

A COLD Approach to Generating Optimal Samples. - Omar Mahmood; José Miguel Hernández-Lobato (CoRR, 2019)

Optimal tuning of weighted kNN- and diffusion-based methods for denoising single cell genomics data. - Andreas Tjärnberg; Omar Mahmood; Christopher A. Jackson; Giuseppe-Antonio Saldi; Kyunghyun Cho; Lionel A. Christiaen; Richard A. Bonneau (PLoS Comput. Biol., 2021)

3D molecule generation by denoising voxel grids. - Pedro O. Pinheiro; Joshua Rackers; Joseph Kleinhenz; Michael Maser; Omar Mahmood; Andrew M. Watkins; Stephen Ra; Vishnu Sresht; Saeed Saremi (NeurIPS, 2023)

Structure-based drug design by denoising voxel grids. - Pedro O. Pinheiro; Arian Rokkum Jamasb; Omar Mahmood; Vishnu Sresht; Saeed Saremi (ICML, 2024)

Structure-based drug design by denoising voxel grids. - Pedro O. Pinheiro; Arian Jamasb; Omar Mahmood; Vishnu Sresht; Saeed Saremi (CoRR, 2024)

NEBULA: Neural Empirical Bayes Under Latent Representations for Efficient and Controllable Design of Molecular Libraries. - Ewa M. Nowara; Pedro O. Pinheiro; Sai Pooja Mahajan; Omar Mahmood; Andrew Martin Watkins; Saeed Saremi; Michael Maser (CoRR, 2024)