Displaying 26 resources
Software resources Software resources

Decentralized-gnn

A package for implementing and simulating decentralized Graph Neural Network algorithms for classification of peer-to-peer nodes.

Category
System architectures, Technology methodologies and landscape
Target audience
ADR Experts and Associations, Researchers and Academic
Source
Adra-e
Software resources Software resources

JGNN library for native Java implementation of graph neural networks

Graph Neural Networks (GNNs) have seen a dramatic increase in popularity thanks to their ability to understand relations between graph nodes.

Category
Technology methodologies and landscape
Target audience
ADR Experts and Associations, Researchers and Academic
Source
Adra-e
Software resources Software resources

Word-Class Embeddings for Multiclass Text Classification

Code for Word-Class Embeddings (WCEs), a form of supervised embeddings especially suited for multiclass text classification.

Category
Semantic knowledge, Technology methodologies and landscape
Target audience
ADR Experts and Associations, Researchers and Academic
Source
Adra-e
Software resources Software resources

CO2A – Contrastive Conditional domain Alignment

A novel unsupervised domain adaptation approach for action recognition from videos, inspired by recent literature on contrastive learning.

Category
Multi-modal interaction, Sensing of motion and mechanical properties
Target audience
ADR Experts and Associations, Researchers and Academic
Source
Adra-e
Software resources Software resources

FeTrIL: Feature Translation for Exemplar-Free Class-Incremental Learning

Exemplar-free class-incremental learning is very challenging due to the negative effect of catastrophic forgetting.

Category
Technology methodologies and landscape
Target audience
ADR Experts and Associations, Researchers and Academic
Source
Adra-e
Software resources Software resources

pygrank

pygrank is an open source framework to define, run and evaluate node ranking algorithms.

Category
Multi-modal interaction
Target audience
ADR Experts and Associations, Private Sector, Researchers and Academic
Source
Adra-e