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Found 6 papers, 2 papers with code
Privacy-Preserving Distributed Learning for Residential Short-Term Load Forecasting
In the realm of power systems, the increasing involvement of residential users in load forecasting applications has heightened concerns about data privacy.
QNNRepair: Quantized Neural Network Repair
It accepts the full-precision and weight-quantized neural networks and a repair dataset of passing and failing tests.
A Survey of Safety and Trustworthiness of Large Language Models through the Lens of Verification and Validation
Large Language Models (LLMs) have exploded a new heatwave of AI for their ability to engage end-users in human-level conversations with detailed and articulate answers across many knowledge domains.
AIREPAIR: A Repair Platform for Neural Networks
We present AIREPAIR, a platform for repairing neural networks.
Privacy-Friendly Peer-to-Peer Energy Trading: A Game Theoretical Approach
Hence, privacy of both sellers and buyers is preserved.
Impact of Local Energy Markets on the Distribution Systems: A Comprehensive Review
In recent years extensive research has been conducted on the development of different models that enable energy trading between prosumers and consumers due to expected high integration of distributed energy resources.
