eScholarship
metadata only
Generating adversarial inputs for a graph neural network model of AC power flow
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Bridging the Gap Between Network Science and Network Systems to Identify and Mitigate Cyber Risk: Identify and Mitigate Backdoor Attacks on Graph Neural Networks and on Complex Systems#169445
- A Standardized Framework for Machine Learning in Power System Protection#1014806
- Momentum-Based Adversarial Attacks and Multi-Level Denoising Defenses in Deep Learning-Based Wind Power Forecasting.#9457
- The President and the Power Grid#464621
- Hybrid safe deep reinforcement learning and model predictive control for power distribution grids management system under uncertainties#643263
Record · ID 683998
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive