Pinned Repositories
ACM-GNN-forked
NeurIPS 2022, Revisiting Heterophily For Graph Neural Networks, official PyTorch implementation for Adaptive Channel Mixing (ACM) GNN framework
AHLC
Our paper is accepted by IJCNN 2021----Automatic CNN Compression Based on Hyper-parameter Learning
CNN-TE
GAT-forked
Graph Attention Networks (https://arxiv.org/abs/1710.10903)
gcn
Implementation of Graph Convolutional Networks in TensorFlow
GCNII-forked
PyTorch implementation of "Simple and Deep Graph Convolutional Networks"
gorilla-forked
Gorilla: An API store for LLMs
Heterophily_and_oversmoothing-forked
Codes for "Two Sides of the Same Coin: Heterophily and Oversmoothing in Graph Convolutional Neural Networks"
HiGCN-forked
avmoldovan's Repositories
avmoldovan/CNN-TE
avmoldovan/ACM-GNN-forked
NeurIPS 2022, Revisiting Heterophily For Graph Neural Networks, official PyTorch implementation for Adaptive Channel Mixing (ACM) GNN framework
avmoldovan/AHLC
Our paper is accepted by IJCNN 2021----Automatic CNN Compression Based on Hyper-parameter Learning
avmoldovan/GAT-forked
Graph Attention Networks (https://arxiv.org/abs/1710.10903)
avmoldovan/gcn
Implementation of Graph Convolutional Networks in TensorFlow
avmoldovan/GCNII-forked
PyTorch implementation of "Simple and Deep Graph Convolutional Networks"
avmoldovan/gorilla-forked
Gorilla: An API store for LLMs
avmoldovan/Heterophily_and_oversmoothing-forked
Codes for "Two Sides of the Same Coin: Heterophily and Oversmoothing in Graph Convolutional Neural Networks"
avmoldovan/HiGCN-forked
avmoldovan/HOG-GCN-forked
avmoldovan/nn-from-scratch
Implementing a Neural Network from Scratch
avmoldovan/OpenDevin-forked
🐚 OpenDevin: Code Less, Make More
avmoldovan/powerful-gnns-forked
How Powerful are Graph Neural Networks?
avmoldovan/pygcn-forked
Graph Convolutional Networks in PyTorch
avmoldovan/ssp-forked
avmoldovan/SWE-agent-forked
SWE-agent takes a GitHub issue and tries to automatically fix it, using GPT-4, or your LM of choice. It solves 12.29% of bugs in the SWE-bench evaluation set and takes just 1.5 minutes to run.