graph-neural-networks

Papers about graph transformers.

A Large-Scale Multimodal Car Dataset with Computational Fluid Dynamics Simulations and Deep Learning Benchmarks

Segment Anything Model for large-scale, vectorized road network extraction from aerial imagery. CVPRW 2024

Source code for GNN-LSPE (Graph Neural Networks with Learnable Structural and Positional Representations), ICLR 2022

Code for the paper 'Learning TSP Requires Rethinking Generalization' (CP 2021)

A curated list of papers on pre-training for graph neural networks (Pre-train4GNN).

This repository contains all the work that I regularly did and studied from Medium blogs, several research papers, and other Repos (related/unrelated to the research papers).

Notebooks for the Practicals at the Deep Learning Indaba 2022.

autoupdate paper list

The official implementation of DiffAbXL benchmarked in the paper "Exploring Log-Likelihood Scores for Ranking Antibody Sequence Designs", formerly titled "Benchmarking Generative Models for Antibody Design".

ECML 2019: Graph Neural Networks for Multi-Label Classification

Official source code for "Graph Neural Networks for Learning Equivariant Representations of Neural Networks". In ICLR 2024 (oral).

Relational Graph Transformer

A geometric deep learning framework (Geometric Transformers) for predicting protein interface contacts. (ICLR 2022)

Transformers are Graph Neural Networks!

Code snippets and solutions for the Introduction to Deep Learning and Neural Networks Course hosted in educative.io

A curated list of papers on graph transfer learning (GTL).

Graph database library that allows you to store, analyze, and search through your data in a graph format. By using the Universal Sentence Encoder, it provides an efficient and semantic approach to handle text data. 📚🧠🚀

Measuring generalization properties of graph neural networks