Notes
  • README
  • Roadmap
  • Graph
    • GraphSAGE
    • DiffPool
    • RRN
    • Relational RL
    • Layerwise Adaptive Sampling
    • Representation Lerning on Graphs: Methods and Applications
    • GAT
    • How Powerful are Graph Neural Networks?
    • Pitfalls of Graph Neural Network Evaluation
    • Spectral Networks and Deep Locally Connected Networks on Graphs
    • Deep Convolutional Networks on Graph-Structured Data
  • Optimizations
    • Neural ODE
  • Tags
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Last updated 6 years ago

Reading list

Neural Ordinary Differential Equations
Note
Code
Representation Learning on Graphs: Methods and Applications
Note
Slides
Recurrent Relational Networks
Note
Website
Inductive Representation Learning on Large Graphs
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Hierarchical Graph Representation Learning with Differentiable Pooling
Note
Code
Deep Graph Infomax
Note
Code
Neural GPUs Learn Algorithms
Note
Code
PDE-Net: Learning PDEs from Data
Note
Code
Embedding Logical Queries on Knowledge Graphs
Note
Relational Deep Reinforcement Learning
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Graph Convolutional Neural Networks for Web-Scale Recommender Systems
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FastGCN: Fast Learning with Graph Convolutional Networks via Importance Sampling
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Graph U-Net
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Towards Sparse Hierarchical Graph Classifiers
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Adaptive Sampling Towards Fast Graph Representation Learning
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Graph Attention Networks
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How Powerful are Graph Neural Networks?
Note
Pitfalls of Graph Neural Network Evaluation
Note
Code
Spectral Networks and Deep Locally Connected Networks on Graphs
Note
Deep Convolutional Networks on Graph-Structured Data
Note
ML beyond Curve Fitting: An Intro to Causal Inference and do-Calculus
The Blessings of Multiple Causes: Causal Inference when you Can't Measure Confounders
Causal Inference 2: Illustrating Interventions via a Toy Example