Double-Gabor Filters Are Independent Components of Small Translation-Invariant Image Patches. - Saeed Saremi; Terrence J. Sejnowski; Tatyana O. Sharpee (Neural Comput., 2013)

Hierarchical model of natural images and the origin of scale invariance. - Saeed Saremi; Terrence J. Sejnowski (Proc. Natl. Acad. Sci. USA, 2013)

On Criticality in High-Dimensional Data. - Saeed Saremi; Terrence J. Sejnowski (Neural Comput., 2014)

The Wilson Machine for Image Modeling. - Saeed Saremi; Terrence J. Sejnowski (CoRR, 2015)

Correlated Percolation, Fractal Structures, and Scale-Invariant Distribution of Clusters in Natural Images. - Saeed Saremi; Terrence J. Sejnowski (IEEE Trans. Pattern Anal. Mach. Intell., 2016)

Annealed Generative Adversarial Networks. - Arash Mehrjou; Bernhard Schölkopf; Saeed Saremi (CoRR, 2017)

Deep Energy Estimator Networks. - Saeed Saremi; Arash Mehrjou; Bernhard Schölkopf; Aapo Hyvärinen (CoRR, 2018)

On approximating ∇f with neural networks. - Saeed Saremi (CoRR, 2019)

Neural Empirical Bayes. - Saeed Saremi; Aapo Hyvärinen (J. Mach. Learn. Res., 2019)

Provable Robust Classification via Learned Smoothed Densities. - Saeed Saremi; Rupesh Srivastava (CoRR, 2020)

Learning and Inference in Imaginary Noise Models. - Saeed Saremi (CoRR, 2020)

Unnormalized Variational Bayes. - Saeed Saremi (CoRR, 2020)

Automatic design of novel potential 3CLpro and PLpro inhibitors. - Timothy Atkinson 001; Saeed Saremi; Faustino J. Gomez; Jonathan Masci (CoRR, 2021)

Multimeasurement Generative Models. - Saeed Saremi; Rupesh Kumar Srivastava (ICLR, 2022)

PropertyDAG: Multi-objective Bayesian optimization of partially ordered, mixed-variable properties for biological sequence design. - Ji Won Park; Samuel Stanton; Saeed Saremi; Andrew M. Watkins; Henri Dwyer; Vladimir Gligorijevic; Richard Bonneau; Stephen Ra; Kyunghyun Cho (CoRR, 2022)

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)

Universal Smoothed Score Functions for Generative Modeling. - Saeed Saremi; Rupesh Kumar Srivastava; Francis R. Bach (CoRR, 2023)

Protein Discovery with Discrete Walk-Jump Sampling. - Nathan C. Frey; Daniel Berenberg; Karina Zadorozhny; Joseph Kleinhenz; Julien Lafrance-Vanasse; Isidro Hötzel; Yan Wu 027; Stephen Ra; Richard Bonneau; Kyunghyun Cho; Andreas Loukas; Vladimir Gligorijevic; et al. (ICLR, 2024)

Chain of Log-Concave Markov Chains. - Saeed Saremi; Ji Won Park; Francis R. Bach (ICLR, 2024)

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

Score-based 3D molecule generation with neural fields. - Matthieu Kirchmeyer; Pedro O. Pinheiro; Saeed Saremi (NeurIPS, 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)

JAMUN: Transferable Molecular Conformational Ensemble Generation with Walk-Jump Sampling. - Ameya Daigavane; Bodhi P. Vani; Saeed Saremi; Joseph Kleinhenz; Joshua Rackers (CoRR, 2024)

Sampling Binary Data by Denoising through Score Functions. - Francis R. Bach; Saeed Saremi (CoRR, 2025)