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GitHub2y
caixunshiren/GCNGDE_Simulation_for_EEG_analysis: Analyzing EEG dataset using graph convolutional neural network and graph differential equations. - GitHub
The accuracy plot is shown below. It is interesting to see how each brain graph progress, which is different for each neural network. Below shows the brain graph progression for patient 958. From the ...
Semiconductor Engineering3mon
Physics Simulation With Graph Neural Networks Targeting Mobile - Semiconductor Engineering
The Encoder processes particle positions into relevant features in a GraphTensor structure and embeds them into the tfgnn.HIDDEN_STATE vector. ... Based on our results, we recommend Graph Neural ...
GitHub1mon
GitHub - brianlsy98/DICE: Device-level Integrated Circuits Encoder with Graph Contrastive Pretraining
DICE adopts a simulation-free pretraining approach based on graph contrastive learning, leveraging two novel graph augmentation techniques. Experimental results demonstrate substantial performance ...
IEEE8mon
Simulation of PCM/FM Telemetry Data Encoder Based on IRIG-106 Standard in Matlab Simulink - IEEE Xplore
The telemetry data encoder, a component of the PCM/FM transmitter system in the rocket telemetry (TM), adheres to the IRIG-106 standard. It’s used to gather data from sensors that monitor various ...
marktechpost1y
Enhancing Graph Data Embeddings with Machine Learning: The Deep Manifold Graph Auto-Encoder (DMVGAE/DMGAE) Approach - MarkTechPost
Consequently, they present the Deep Manifold (Variational) Graph Auto-Encoder (DMVGAE/DMGAE) method for attributed graph embedding to enhance the stability and quality of representations. They ...
IEEE6mon
Accelerate SEU Simulation-Based Fault Injection With Spatio-Temporal Graph Convolutional Networks - IEEE Xplore
Evaluating the sensitivity of circuits to Single Event Upset (SEU) faults has become increasingly important and challenging due to the growing complexity of circuits. Simulation-based fault injection ...