3 citations · 4 across the 4 of their papers we have counts for
4 papers
Towards Physics-informed Diffusion for Anomaly Detection in Trajectories
Arun Sharma, Mingzhou Yang, Majid Farhadloo +3
Given trajectory data, a domain-specific study area, and a user-defined threshold, we aim to find anomalous trajectories indicative of possible GPS spoofing (e.g., fake trajectory)…
Physics-based machine learning framework for predicting NOx emissions from compression ignition engines using on-board diagnostics data
Harish Panneer Selvam, Bharat Jayaprakash, Yan Li +2
This work presents a physics-based machine learning framework to predict and analyze oxides of nitrogen (NOx) emissions from compression-ignition engine-powered vehicles using on-b…
Towards Physics-Guided Foundation Models
Majid Farhadloo, Arun Sharma, Mingzhou Yang +3
Traditional foundation models are pre-trained on broad datasets to reduce the training resources (e.g., time, energy, labeled samples) needed for fine-tuning a wide range of downst…
A Survey on Solving and Discovering Differential Equations Using Deep Neural Networks
Hyeonjung, Jung, Jayant Gupta +6
Ordinary and partial differential equations (DE) are used extensively in scientific and mathematical domains to model physical systems. Current literature has focused primarily on…