Singhal, Raghav

11 publications

ICML 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

ICLRW 2025 FedEx-LoRA: Exact Aggregation for Federated and Efficient Fine-Tuning of Foundation Models Raghav Singhal, Kaustubh Ponkshe, Praneeth Vepakomma

ICLRW 2025 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

TMLR 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

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

NeurIPSW 2024 FedEx-LoRA: Exact Aggregation for Federated Parameter-Efficient Fine-Tuning of Foundation Models Raghav Singhal, Kaustubh Ponkshe, Praneeth Vepakomma

NeurIPSW 2024 M3CoL: Harnessing Shared Relations via Multimodal Mixup Contrastive Learning for Multimodal Classification Raja Kumar, Raghav Singhal, Pranamya Prashant Kulkarni, Deval Mehta, Kshitij Sharad Jadhav

NeurIPSW 2024 N Multipliers for N Bits: Learning Bit Multipliers for Non-Uniform Quantization Raghav Singhal, Anmol Biswas, Sivakumar Elangovan, Shreyas Sabnis, Udayan Ganguly

NeurIPSW 2024 Self-Supervised Pre-Training of Spiking Neural Networks by Contrasting Events and Frames Raghav Singhal, Jan Finkbeiner, Emre Neftci

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

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