D2L_Attention_Mechanisms_in_TF
pytorch-GAT
| D2L_Attention_Mechanisms_in_TF | pytorch-GAT | |
|---|---|---|
| 7 | 14 | |
| 12 | 2,305 | |
| - | - | |
| 0.0 | 0.0 | |
| over 2 years ago | over 1 year ago | |
| Jupyter Notebook | Jupyter Notebook | |
| - | MIT License |
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D2L_Attention_Mechanisms_in_TF
- [P] Tensorflow 2 code for Attention Mechanisms chapter of Dive into Deep Learning (D2L) book.
- Project [P] Tensorflow 2 code for Attention Mechanisms chapter of Dive into Deep Learning (D2L) book.
- Tensorflow 2 code for Attention Mechanisms chapter of Dive into Deep Learning (D2L) book.
- [P] Tensorflow 2 code for Attention Mechanisms chapter of Dive into Deep Learning (D2L) book. Github link: https://github.com/biswajitsahoo1111/D2L_Attention_Mechanisms_in_TF
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?
NLP-With-PyTorch - My NLP experiments using PyTorch to solve some common NLP problems with advanced and state of the art deep learning techniques.
pytorch-seq2seq - Tutorials on implementing a few sequence-to-sequence (seq2seq) models with PyTorch and TorchText.
TokenCut - (CVPR 2022) Pytorch implementation of "Self-supervised transformers for unsupervised object discovery using normalized cut"
gan-vae-pretrained-pytorch - Pretrained GANs + VAEs + classifiers for MNIST/CIFAR in pytorch.
gpt-mini - Yet another minimalistic Tensorflow (re-)re-implementation of Karpathy's Pytorch re-implementation of the OpenAI GPT (Generative Pretrained Transformer).
GAT - Graph Attention Networks (https://arxiv.org/abs/1710.10903)
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.
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