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01/21/2023
Compact Optimization Learning for AC Optimal Power Flow
This paper reconsiders end-to-end learning approaches to the Optimal Pow...
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11/28/2022
Confidence-Aware Graph Neural Networks for Learning Reliability Assessment Commitments
Reliability Assessment Commitment (RAC) Optimization is increasingly imp...
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08/18/2022
Self-Supervised Primal-Dual Learning for Constrained Optimization
This paper studies how to train machine-learning models that directly ap...
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04/02/2022
Risk-Aware Control and Optimization for High-Renewable Power Grids
The transition of the electrical power grid from fossil fuels to renewab...
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12/27/2021
Learning Optimization Proxies for Large-Scale Security-Constrained Economic Dispatch
The Security-Constrained Economic Dispatch (SCED) is a fundamental optim...
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09/21/2021
Homography augumented momentum constrastive learning for SAR image retrieval
Deep learning-based image retrieval has been emphasized in computer visi...
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04/14/2021
Deep Data Density Estimation through Donsker-Varadhan Representation
Estimating the data density is one of the challenging problems in deep l...
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05/05/2020
Interpreting Rate-Distortion of Variational Autoencoder and Using Model Uncertainty for Anomaly Detection
Building a scalable machine learning system for unsupervised anomaly det...
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06/27/2019