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Found 8 papers, 2 papers with code
MATNilm: Multi-appliance-task Non-intrusive Load Monitoring with Limited Labeled Data
Non-intrusive load monitoring (NILM) identifies the status and power consumption of various household appliances by disaggregating the total power usage signal of an entire house.
CelebA-Spoof Challenge 2020 on Face Anti-Spoofing: Methods and Results
It is the largest face anti-spoofing dataset in terms of the numbers of the data and the subjects.
Encoding Frequency Constraints in Preventive Unit Commitment Using Deep Learning with Region-of-Interest Active Sampling
Frequency-constrained unit commitment (FCUC) is proposed to address this challenge.
Hybrid Imitation Learning for Real-Time Service Restoration in Resilient Distribution Systems
Self-healing capability is one of the most critical factors for a resilient distribution system, which requires intelligent agents to automatically perform restorative actions online, including network reconfiguration and reactive power dispatch.
Deep Active Learning for Solvability Prediction in Power Systems
Traditional methods for solvability region analysis can only have inner approximations with inconclusive conservatism.
Robust Synthesis of Wind Turbine Generators to Support Microgrid Frequency Considering Linearization-Induced Uncertainty
The capability to switch between grid-connected and islanded modes has promoted adoption of microgrid technology for powering remote locations.
Approximating Trajectory Constraints with Machine Learning -- Microgrid Islanding with Frequency Constraints
In this paper, we introduce a deep learning aided constraint encoding method to tackle the frequency-constraint microgrid scheduling problem.
Singular Perturbation-based Large-Signal Order Reduction of Microgrids for Stability and Accuracy Synthesis with Control
Higher-level controller design and stability analysis of such high-order systems are usually intractable and computation-costly.
