Publications & Preprints

Raghav Singhal, Zachary Horvitz, Ryan Teehan, Mengye Ren, Zhou Yu, Kathleen McKeown, Rajesh Ranganath. A General Framework for Inference-time Scaling and Steering of Diffusion Models

Raghav Singhal, Mark Goldstein, Rajesh Ranganath. What’s the score? Automated Denoising Score Matching for Nonlinear Diffusions. ICML 2024

Chen-YU Yen, Raghav Singhal, Umang Sharma, Rajesh Ranganath, Sumit Chopra, Lerrel Pinto. Adaptive Sampling of k-Space in Magnetic Resonance for Rapid Pathology Prediction. ICML 2024

Raghav Singhal, Mark Goldstein, Rajesh Ranganath. Where to diffuse, how to diffuse, and how to get back: Automated learning for multivariate diffusions. ICLR 2023

Raghav Singhal, Mukund Sudarshan, Hersh Chandarana, Daniel K. Sodickson, Rajesh Ranganath, Sumit Chopra. On the feasibility of machine learning augmented magnetic resonance for point-of-care identification of disease. ArXiv 2023

Raghav Singhal, Mukund Sudarshan, Luke Ginocchio, Angela Tong, Hersh Chandarana, Daniel Sodickson, Rajesh Ranganath, Sumit Chopra. Accelerated MR screenings with direct k-space classification . ISMRM 2022

Raghav Singhal, Xintian Han, Saad Lahlou, Rajesh Ranganath. Kernelized complete conditional Stein discrepancy . Arxiv 2020