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07/28/2023
Dynamic PlenOctree for Adaptive Sampling Refinement in Explicit NeRF
The explicit neural radiance field (NeRF) has gained considerable intere...
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06/29/2023
Laxity-Aware Scalable Reinforcement Learning for HVAC Control
Demand flexibility plays a vital role in maintaining grid balance, reduc...
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12/30/2022
Pontryagin Optimal Controller via Neural Networks
Solving real-world optimal control problems are challenging tasks, as th...
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12/01/2022
Enabling Fast Unit Commitment Constraint Screening via Learning Cost Model
Unit commitment (UC) are essential tools to transmission system operator...
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11/27/2022
BEAR: Physics-Principled Building Environment for Control and Reinforcement Learning
Recent advancements in reinforcement learning algorithms have opened doo...
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04/14/2022
Learning Task-Aware Energy Disaggregation: a Federated Approach
We consider the problem of learning the energy disaggregation signals fo...
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10/18/2021
Improving Robustness of Reinforcement Learning for Power System Control with Adversarial Training
Due to the proliferation of renewable energy and its intrinsic intermitt...
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03/13/2019
Forecasting Spatio-Temporal Renewable Scenarios: a Deep Generative Approach
The operation and planning of large-scale power systems are becoming mor...
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09/20/2018
IntelligentCrowd: Mobile Crowdsensing via Multi-agent Reinforcement Learning
The prosperity of smart mobile devices has made mobile crowdsensing (MCS...
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02/02/2018