Publications (43)
Kairos: A Regret-Aware Native World-Action Model Stack for Physical AI
Kairos Team, Fei Wang, Shan You +21
We introduce \textbf{Kairos}, a regret-aware native world-action model stack for Physical AI. Kairos is motivated by the view that a physical world model should not aim to fully si…
Chance Constrained Optimal Power Flow Using the Inner-Outer Approximation Approach
Erfan Mohagheghi, Abebe Geletu, Nils Bremser +3
In recent years, there has been a huge trend to penetrate renewable energy sources into energy networks. However, these sources introduce uncertain power generation depending on en…
Learning Deep Models from Synthetic Data for Extracting Dolphin Whistle Contours
Pu Li, Xiaobai Liua, K. J. Palmer +8
We present a learning-based method for extracting whistles of toothed whales (Odontoceti) in hydrophone recordings. Our method represents audio signals as time-frequency spectrogra…
Real-Time Dynamic Optimal Power Flow in Electric Vehicles Considering the Lifetime of the Components in the E-Powertrain
Erfan Mohagheghi, Joan Gubianes Gasso, Pu Li
Different types of energy sources (e.g., batteries, supercapacitors, fuel cells) can be utilized in electric vehicles to store and provide energy in the e-powertrain through power…
An Once-for-All Budgeted Pruning Framework for ConvNets Considering Input Resolution
Wenyu Sun, Jian Cao, Pengtao Xu +2
We propose an efficient once-for-all budgeted pruning framework (OFARPruning) to find many compact network structures close to winner tickets in the early training stage considerin…
Community Detection in Large-Scale Complex Networks via Structural Entropy Game
Yantuan Xian, Pu Li, Hao Peng +3
Community detection is a critical task in graph theory, social network analysis, and bioinformatics, where communities are defined as clusters of densely interconnected nodes. Howe…