IEEE

PyTorch Ecosystem for Graph Neural Networks: A Comprehensive Review

Abstract: Deep learning has witnessed rapid progress through frameworks such as PyTorch, which has become the dominant choice for researchers and practitioners due to its dynamic computation, ...
GitHub

Multi-View Conditional Information Bottleneck

Multi-View Conditional Information Bottleneck (MVCIB) is a novel architecture for pre-training Graph Neural Networks on 2D and 3D molecular structures and developed by NS Lab, CUK based on pure ...
marktechpost

A Coding Implementation to Build Neural Memory Agents with Differentiable Memory, Meta-Learning, and Experience Replay for Continual Adaptation in Dynamic Environments

In this tutorial, we explore how neural memory agents can learn continuously without forgetting past experiences. We design a memory-augmented neural network that integrates a Differentiable Neural ...
Frontiers

Inferred global dense residue transition graphs from primary structure sequences enable protein interaction prediction via directed graph convolutional neural networks

Accurate prediction of protein-protein interactions (PPIs) is crucial for understanding cellular functions and advancing the development of drugs. While existing in-silico methods leverage direct ...
Scientific Research Publishing

Lin, J., Zhao, Y., Huang, W., Liu, C. and Pu, H. (2020) Domain Knowledge Graph-Based Research Progress of Knowledge Representation. Neural Computing and Applications, 33, 681-690.

ABSTRACT: Knowledge Graph (KG) and neural network (NN) based Question-answering (QA) systems have evolved into the realm of intelligent information retrieval as they have been able to reach a high ...
marktechpost

Step by Step Coding Guide to Build a Neural Collaborative Filtering (NCF) Recommendation System with PyTorch

This tutorial will walk you through using PyTorch to implement a Neural Collaborative Filtering (NCF) recommendation system. NCF extends traditional matrix factorisation by using neural networks to ...