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)

SupSiam: Non-contrastive Auxiliary Loss for Learning from Molecular Conformers. - Michael Maser; Ji Won Park; Joshua Yao-Yu Lin; Jae Hyeon Lee; Nathan C. Frey; Andrew M. Watkins (CoRR, 2023)

MoleCLUEs: Optimizing Molecular Conformers by Minimization of Differentiable Uncertainty. - Michael Maser; Natasa Tagasovska; Jae Hyeon Lee; Andrew M. Watkins (CoRR, 2023)

BOtied: Multi-objective Bayesian optimization with tied multivariate ranks. - Ji Won Park; Natasa Tagasovska; Michael Maser; Stephen Ra; Kyunghyun Cho (ICML, 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)

Do we need equivariant models for molecule generation? - Ewa M. Nowara; Joshua Rackers; Patricia Suriana; Pan Kessel; Max Shen 002; Andrew Martin Watkins; Michael Maser (CoRR, 2025)