Graph Attention Network Project Walkthrough
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In this video, I walk you through my recently open-source GAT project. I focus on 2 potential pain points in the implementation and I also highlight some of my previous projects you could find interesting.
You'll learn about:
✔️ Cora dataset
✔️ Highly-optimized GAT implementation
✔️ Other exciting DL projects you could play with
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✅ My GAT project: https://github.com/gordicaleksa/pytorch-GAT
✅ Naive neural style transfer for videos: https://github.com/gordicaleksa/py…
Watch on YouTube ↗
(saves to browser)
Chapters (15)
Intro to GAT project
0:35
My other deep learning projects
4:00
README walkthrough
7:35
Node degree statistics
10:10
Entropy histograms
12:05
t-SNE plots
12:50
Graph drawing layout
14:00
Jupyter walkthrough
15:22
Understanding Cora dataset
18:19
Feature vectors and labels
20:00
Building the edge index
22:40
Toy example (understanding the implementation)
29:00
Lifting
32:50
Neighborhood aware softmax and aggregate
38:18
Outro, exciting deep learning projects
Playlist
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Intro | Neural Style Transfer #1
Aleksa Gordić - The AI Epiphany
Basic Theory | Neural Style Transfer #2
Aleksa Gordić - The AI Epiphany
Optimization method | Neural Style Transfer #3
Aleksa Gordić - The AI Epiphany
Advanced Theory | Neural Style Transfer #4
Aleksa Gordić - The AI Epiphany
Anyone can make deepfakes now!
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What is Computer Vision? | The Art of Creating Seeing Machines
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Feed-forward method | Neural Style Transfer #5
Aleksa Gordić - The AI Epiphany
Alan Turing | Computing Machinery and Intelligence
Aleksa Gordić - The AI Epiphany
Feed-forward method (training) | Neural Style Transfer #6
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What is Google Deep Dream? (Basic Theory) | Deep Dream Series #1
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Semantic Segmentation in PyTorch | Neural Style Transfer #7
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How to get started with Machine Learning
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How to learn PyTorch? (3 easy steps) | 2021
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PyTorch or TensorFlow?
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3 Machine Learning Projects For Beginners (Highly visual) | 2021
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Machine Learning Projects (Intermediate level) | 2021
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Cheapest (0$) Deep Learning Hardware Options | 2021
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How to learn deep learning? (Transformers Example)
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How do transformers work? (Attention is all you need)
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Developing a deep learning project (case study on transformer)
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Vision Transformer (ViT) - An image is worth 16x16 words | Paper Explained
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GPT-3 - Language Models are Few-Shot Learners | Paper Explained
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Google DeepMind's AlphaFold 2 explained! (Protein folding, AlphaFold 1, a glimpse into AlphaFold 2)
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Attention Is All You Need (Transformer) | Paper Explained
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Graph Attention Networks (GAT) | GNN Paper Explained
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Graph Convolutional Networks (GCN) | GNN Paper Explained
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Graph SAGE - Inductive Representation Learning on Large Graphs | GNN Paper Explained
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PinSage - Graph Convolutional Neural Networks for Web-Scale Recommender Systems | Paper Explained
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OpenAI CLIP - Connecting Text and Images | Paper Explained
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Temporal Graph Networks (TGN) | GNN Paper Explained
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Graph Neural Network Project Update! (I'm coding GAT from scratch)
Aleksa Gordić - The AI Epiphany
Graph Attention Network Project Walkthrough
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How to get started with Graph ML? (Blog walkthrough)
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DQN - Playing Atari with Deep Reinforcement Learning | RL Paper Explained
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AlphaGo - Mastering the game of Go with deep neural networks and tree search | RL Paper Explained
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DeepMind's AlphaGo Zero and AlphaZero | RL paper explained
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OpenAI - Solving Rubik's Cube with a Robot Hand | RL paper explained
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MuZero - Mastering Atari, Go, Chess and Shogi by Planning with a Learned Model | RL Paper explained
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EfficientNetV2 - Smaller Models and Faster Training | Paper explained
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Implementing DeepMind's DQN from scratch! | Project Update
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MLP-Mixer: An all-MLP Architecture for Vision | Paper explained
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DeepMind's Android RL Environment - AndroidEnv
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When Vision Transformers Outperform ResNets without Pretraining | Paper Explained
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Non-Parametric Transformers | Paper explained
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Chip Placement with Deep Reinforcement Learning | Paper Explained
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Text Style Brush - Transfer of text aesthetics from a single example | Paper Explained
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Graphormer - Do Transformers Really Perform Bad for Graph Representation? | Paper Explained
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GANs N' Roses: Stable, Controllable, Diverse Image to Image Translation | Paper Explained
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VQ-VAEs: Neural Discrete Representation Learning | Paper + PyTorch Code Explained
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VQ-GAN: Taming Transformers for High-Resolution Image Synthesis | Paper Explained
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Multimodal Few-Shot Learning with Frozen Language Models | Paper Explained
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Focal Transformer: Focal Self-attention for Local-Global Interactions in Vision Transformers
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AudioCLIP: Extending CLIP to Image, Text and Audio | Paper Explained
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RMA: Rapid Motor Adaptation for Legged Robots | Paper Explained
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DALL-E: Zero-Shot Text-to-Image Generation | Paper Explained
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Channel Update: vacation, leaving Microsoft, approaching 10k subs and more!
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DETR: End-to-End Object Detection with Transformers | Paper Explained
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DINO: Emerging Properties in Self-Supervised Vision Transformers | Paper Explained!
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DeepMind DetCon: Efficient Visual Pretraining with Contrastive Detection | Paper Explained
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Do Vision Transformers See Like Convolutional Neural Networks? | Paper Explained
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DeepCamp AI