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cs.AI2026
Residual Modeling for High-Fidelity Learned Compression of Scientific Data
Liangji Zhu, Sanjay Ranka, Anand Rangarajan
Lossy compression is essential for massive spatiotemporal data from scientific simulations. Learned compressors can achieve high compression ratios at moderate accuracy targets, bu…
cs.AI2025
Evaluating Generative Vehicle Trajectory Models for Traffic Intersection Dynamics
Yash Ranjan, Rahul Sengupta, Anand Rangarajan +1
Traffic Intersections are vital to urban road networks as they regulate the movement of people and goods. However, they are regions of conflicting trajectories and are prone to acc…
cs.AI2025
IntTrajSim: Trajectory Prediction for Simulating Multi-Vehicle driving at Signalized Intersections
Yash Ranjan, Rahul Sengupta, Anand Rangarajan +1
Traffic simulators are widely used to study the operational efficiency of road infrastructure, but their rule-based approach limits their ability to mimic real-world driving behavi…