Kernelized Complete Conditional Stein Discrepancy. - Raghav Singhal; Saad Lahlou; Rajesh Ranganath (CoRR, 2019)

A Novel HOC-Immersed Interface Approach For Elliptic Problems. - Raghav Singhal; Jiten C. Kalita (CoRR, 2021)

An efficient explicit jump HOC immersed interface approach for transient incompressible viscous flows. - Raghav Singhal; Jiten C. Kalita (CoRR, 2022)

Where to Diffuse, How to Diffuse, and How to Get Back: Automated Learning for Multivariate Diffusions. - Raghav Singhal; Mark Goldstein; Rajesh Ranganath (ICLR, 2023)

Translation and Scale Invariance for Event-Based Object tracking. - Jens Egholm Pedersen; Raghav Singhal; Jörg Conradt (NICE, 2023)

On the Feasibility of Machine Learning Augmented Magnetic Resonance for Point-of-Care Identification of Disease. - Raghav Singhal; Mukund Sudarshan; Anish Mahishi; Sri Kaushik; Luke Ginocchio; Angela Tong; Hersh Chandarana; Daniel K. Sodickson; Rajesh Ranganath; Sumit Chopra (CoRR, 2023)

Comprehensive study of forced convection over a heated elliptical cylinder with varying angle of incidences to uniform free stream. - Raghav Singhal; Sailen Dutta; Jiten C. Kalita (CoRR, 2023)

Enhanced regularization for on-chip training using analog and temporary memory weights. - Raghav Singhal; Vivek Saraswat; Shreyas Deshmukh; Sreenivas Subramoney; Laxmeesha Somappa; Maryam Shojaei Baghini; Udayan Ganguly (Neural Networks, 2023)

Gecko adhesion based sea star crawler robot. - Sampada Acharya; Peter Roberts; Tejas Rane; Raghav Singhal; Peize Hong; Viraj Ranade; Carmel Majidi; Victoria A. Webster-Wood; B. Reeja-Jayan (Frontiers Robotics AI, 2023)

What's the score? Automated Denoising Score Matching for Nonlinear Diffusions. - Raghav Singhal; Mark Goldstein; Rajesh Ranganath (ICML, 2024)

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

Temporal and Spatial Reservoir Ensembling Techniques for Liquid State Machines. - Anmol Biswas; Sharvari Ashok Medhe; Raghav Singhal; Udayan Ganguly (ICONS, 2024)

Harnessing Shared Relations via Multimodal Mixup Contrastive Learning for Multimodal Classification. - Raja Kumar; Raghav Singhal; Pranamya Prashant Kulkarni; Deval Mehta; Kshitij S. Jadhav (CoRR, 2024)

Exact Aggregation for Federated and Efficient Fine-Tuning of Foundation Models. - Raghav Singhal; Kaustubh Ponkshe; Praneeth Vepakomma (CoRR, 2024)

Initialization using Update Approximation is a Silver Bullet for Extremely Efficient Low-Rank Fine-Tuning. - Kaustubh Ponkshe; Raghav Singhal; Eduard Gorbunov; Alexey Tumanov; Samuel Horváth; Praneeth Vepakomma (CoRR, 2024)

FedEx-LoRA: Exact Aggregation for Federated and Efficient Fine-Tuning of Large Language Models. - Raghav Singhal; Kaustubh Ponkshe; Praneeth Vepakomma (ACL (1), 2025)

M3CoL: Harnessing Shared Relations via Multimodal Mixup Contrastive Learning for Multimodal Classification. - Raja Kumar; Raghav Singhal; Pranamya Prashant Kulkarni; Deval Mehta; Kshitij Sharad Jadhav (Trans. Mach. Learn. Res., 2025)

A General Framework for Inference-time Scaling and Steering of Diffusion Models. - Raghav Singhal; Zachary Horvitz; Ryan Teehan; Mengye Ren; Zhou Yu; Kathleen McKeown; Rajesh Ranganath (CoRR, 2025)

Fed-SB: A Silver Bullet for Extreme Communication Efficiency and Performance in (Private) Federated LoRA Fine-Tuning. - Raghav Singhal; Kaustubh Ponkshe; Rohit Vartak; Lav R. Varshney; Praneeth Vepakomma (CoRR, 2025)

Regularization-based Framework for Quantization-, Fault- and Variability-Aware Training. - Anmol Biswas; Raghav Singhal; Sivakumar Elangovan; Shreyas Sabnis; Udayan Ganguly (CoRR, 2025)

Jacobian-Free Newton-Krylov with a globalization method for solving groundwater flow models of multi-layer aquifer systems. - Raghav Singhal; Emin C. Dogrul; Zhaojun Bai (CoRR, 2025)

Safety Subspaces are Not Distinct: A Fine-Tuning Case Study. - Kaustubh Ponkshe; Shaan Shah; Raghav Singhal; Praneeth Vepakomma (CoRR, 2025)

ABBA: Highly Expressive Hadamard Product Adaptation for Large Language Models. - Raghav Singhal; Kaustubh Ponkshe; Rohit Vartak; Praneeth Vepakomma (CoRR, 2025)