GitHub

Event-Driven Spiking Neural Network Accelerator for FPGA

This project implements a complete event-driven spiking neural network (SNN) accelerator on FPGA with seamless PyTorch integration for training and deployment. The design uses Accumulate-only (AC) ...
IEEE

Leveraging Graph Neural Networks to Decode Music-Induced Emotions from EEG

Abstract: Decoding emotion processing from electroencephalogram (EEG) signals is challenging yet promising. We investigate the use of Graph Neural Networks (GNNs) for interpreting EEG data.
IEEE

Scaling Graph Neural Networks for Particle Track Reconstruction

Abstract: Particle track reconstruction is an important problem in high-energy physics (HEP), necessary to study properties of subatomic particles. Traditional track reconstruction algorithms scale ...
Scientific American

Do Brain-Decoding Devices Threaten People’s Privacy?

Before a car crash in 2008 left her paralysed from the neck down, Nancy Smith enjoyed playing the piano. Years later, Smith started making music again, thanks to an implant that recorded and analysed ...
Hosted on MSN

Network in Network (NiN) Explained – Deep Neural Network Tutorial with PyTorch

Learn how Network in Network (NiN) architectures work and how to implement them using PyTorch. This tutorial covers the concept, benefits, and step-by-step coding examples to help you build better ...
Scientific Research Publishing

Graph Neural Networks for Anomaly Detection in Cloud Infrastructure ()

Cloud infrastructure anomalies cause significant downtime and financial losses (estimated at $2.5 M/hour for major services). Traditional anomaly detection methods fail to capture complex dependencies ...
C&EN

Multilevel Fusion Graph Neural Network for Molecule Property Prediction

The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acs.jcim.5c01525. Efficiency analysis of different normalization strategies ...