IEEE

Autoencoder-Augmented Graph Neural Networks for Accurate and Scalable Structure Recognition in Analog/Mixed-Signal Schematics

Abstract: The increasing complexity of Analog/Mixed-Signal (AMS) schematics has been posing significant challenges in structure recognition, particularly in the intellectual property (IP) industry, ...
IEEE

HyperGCN: Interpreting Hyperscanning EEG Signals for Common Multi-Task Classification Using Graph Convolutional Networks

Abstract: EEG hyperscanning employs electroencephalography (EEG) activity to simultaneously monitor the brain activities of several individuals as they interact. During hyperscanning research, ...
GitHub

Memento MCP: A Knowledge Graph Memory System for LLMs

Scalable, high performance knowledge graph memory system with semantic retrieval, contextual recall, and temporal awareness. Provides any LLM client that supports the model context protocol (e.g., ...
Frontiers

Enhancing underwater acoustic orthogonal frequency division multiplexing based channel estimation: a robust convolution-recurrent neural network framework with dynamic signal ...

Introduction: Underwater acoustic (UWA) communication systems confront significant challenges due to the unique, dynamic, and unpredictable nature of acoustic channels, which are impacted by low ...