35 citations · 48 across the 28 of their papers we have counts for
5 papers · 1 filter
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…
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…
TGDT: A Temporal Graph-based Digital Twin for Urban Traffic Corridors
Nooshin Yousefzadeh, Rahul Sengupta, Jeremy Dilmore +1
Urban congestion at signalized intersections leads to significant delays, economic losses, and increased emissions. Existing deep learning models often lack spatial generalizabilit…
Guaranteed Conditional Diffusion: 3D Block-based Models for Scientific Data Compression
Jaemoon Lee, Xiao Li, Liangji Zhu +2
This paper proposes a new compression paradigm -- Guaranteed Conditional Diffusion with Tensor Correction (GCDTC) -- for lossy scientific data compression. The framework is based o…
A General Framework for Error-controlled Unstructured Scientific Data Compression
Qian Gong, Zhe Wang, Viktor Reshniak +10
Data compression plays a key role in reducing storage and I/O costs. Traditional lossy methods primarily target data on rectilinear grids and cannot leverage the spatial coherence…