how_attentive_are_gats
pytorch-GAT
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| how_attentive_are_gats | pytorch-GAT | |
|---|---|---|
| 1 | 14 | |
| 275 | 2,222 | |
| 6.2% | - | |
| 0.0 | 0.0 | |
| about 2 years ago | over 1 year ago | |
| Python | Jupyter Notebook | |
| - | MIT License |
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how_attentive_are_gats
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Graph Attention Networks (GAT) v2 implementation with side-by-side notes
Code for https://arxiv.org/abs/2105.14491 found: https://github.com/tech-srl/how_attentive_are_gats
pytorch-GAT
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[D] Graph neural networks
This repo has a nice hands-on walkthrough: https://github.com/gordicaleksa/pytorch-GAT
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[Discussion] Who are some good deep learning YouTubers?
Maybe: https://youtube.com/c/TheAIEpiphany
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Any resources to learn MDPs and finally complex POMDPs?
I would suggest these three resources: 1: Richard Sutton’s book 2:Reinforcement learning lecture series by deep mind 3:Deep RL lectures by deep mind 4: spinning up by open Ai -> very good resource for key research papers. Try to read and then implement them 5: Practical RL channel by machine learning with Phil. -> good resource on getting to know how to implement deep RL algorithms 6: Research paper breakdown/ practical DL -> good channel to follow for how to understand latest research papers
- Open-source Graph Attention Network (GAT) project with transductive + inductive Jupiter notebooks !
- Obrazovanje
- Open-source Graph Attention Network (GAT) project with transductive + inductive Jupiter notebooks!
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Graph Attention Network project walkthrough! (recently open-sourced <3 )
GitHub link: https://github.com/gordicaleksa/pytorch-GAT
- Show HN: I'm Open-Sourcing Graph Attention Network (GAT) PyTorch
What are some alternatives?
GAT - Graph Attention Networks (https://arxiv.org/abs/1710.10903)
pytorch-seq2seq - Tutorials on implementing a few sequence-to-sequence (seq2seq) models with PyTorch and TorchText.
transformer-pytorch - Transformer: PyTorch Implementation of "Attention Is All You Need"
gan-vae-pretrained-pytorch - Pretrained GANs + VAEs + classifiers for MNIST/CIFAR in pytorch.
bottleneck - Code for the paper: "On the Bottleneck of Graph Neural Networks and Its Practical Implications"
ydata-profiling - 1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.
CodeSearchNet - Datasets, tools, and benchmarks for representation learning of code.
TokenCut - (CVPR 2022) Pytorch implementation of "Self-supervised transformers for unsupervised object discovery using normalized cut"
pytorch-learn-reinforcement-learning - A collection of various RL algorithms like policy gradients, DQN and PPO. The goal of this repo will be to make it a go-to resource for learning about RL. How to visualize, debug and solve RL problems. I've additionally included playground.py for learning more about OpenAI gym, etc.
2D-Gaussian-Splatting - A 2D Gaussian Splatting paper for no obvious reasons. Enjoy!
graph_nets - Build Graph Nets in Tensorflow