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85 papers · 1 filter
A Methodology for Thermal Limit Bias Predictability Through Artificial Intelligence
Anirudh Tunga, Michael J. Mueterthies, Jonathan Nistor
Nuclear power plant operators face significant challenges due to unpredictable deviations between offline and online thermal limits, a phenomenon known as thermal limit bias, which…
Rethinking Individual Fairness in Deepfake Detection
Aryana Hou, Li Lin, Justin Li +1
Generative AI models have substantially improved the realism of synthetic media, yet their misuse through sophisticated DeepFakes poses significant risks. Despite recent advances i…
Relative Entropy Regularized Reinforcement Learning for Efficient Encrypted Policy Synthesis
Jihoon Suh, Yeongjun Jang, Kaoru Teranishi +1
We propose an efficient encrypted policy synthesis to develop privacy-preserving model-based reinforcement learning. We first demonstrate that the relative-entropy-regularized rein…
Federated Learning for Cyber Physical Systems: A Comprehensive Survey
Minh K. Quan, Pubudu N. Pathirana, Mayuri Wijayasundara +5
The integration of machine learning (ML) in cyber physical systems (CPS) is a complex task due to the challenges that arise in terms of real-time decision making, safety, reliabili…
EnsembleCI: Ensemble Learning for Carbon Intensity Forecasting
Leyi Yan, Linda Wang, Sihang Liu +1
Carbon intensity (CI) measures the average carbon emissions generated per unit of electricity, making it a crucial metric for quantifying and managing the environmental impact. Acc…
On the Effectiveness of Random Weights in Graph Neural Networks
Thu Bui, Carola-Bibiane Schönlieb, Bruno Ribeiro +2
Graph Neural Networks (GNNs) have achieved remarkable success across diverse tasks on graph-structured data, primarily through the use of learned weights in message passing layers.…