3 citations · 4 across the 4 of their papers we have counts for
6 papers
ALF: Spectrally Anchored Latent Flow Matching for Wireless Signal Generation
Yiyang Li, Sai Shankar Narasimhan, Priam Alataris +3
Wireless time-series generation is useful for emerging applications that will drive the adoption and integration of machine learning tasks within next-generation networks, such as…
A Challenge to Build Neuro-Symbolic Video Agents
Sahil Shah, Harsh Goel, Sai Shankar Narasimhan +4
Modern video understanding systems excel at tasks such as scene classification, object detection, and short video retrieval. However, as video analysis becomes increasingly central…
SynDiff-AD: Improving Semantic Segmentation and End-to-End Autonomous Driving with Synthetic Data from Latent Diffusion Models
Harsh Goel, Sai Shankar Narasimhan, Oguzhan Akcin +1
In recent years, significant progress has been made in collecting large-scale datasets to improve segmentation and autonomous driving models. These large-scale datasets are often d…
Constrained Posterior Sampling: Time Series Generation with Hard Constraints
Sai Shankar Narasimhan, Shubhankar Agarwal, Litu Rout +2
Generating realistic time series samples is crucial for stress-testing models and protecting user privacy by using synthetic data. In engineering and safety-critical applications,…
Time Weaver: A Conditional Time Series Generation Model
Sai Shankar Narasimhan, Shubhankar Agarwal, Oguzhan Akcin +2
Imagine generating a city's electricity demand pattern based on weather, the presence of an electric vehicle, and location, which could be used for capacity planning during a winte…
Safe Networked Robotics with Probabilistic Verification
Sai Shankar Narasimhan, Sharachchandra Bhat, Sandeep P. Chinchali
Autonomous robots must utilize rich sensory data to make safe control decisions. To process this data, compute-constrained robots often require assistance from remote computation,…