graph-networks
A list of interesting graph neural networks (GNN) links with a primary interest in recommendations and tensorflow that is continually updated and refined
https://github.com/yazdotai/graph-networks
Last synced: about 9 hours ago
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Articles
- A Gentle Introduction to Graph Neural Networks (Basics, DeepWalk, and GraphSage)
- A Gentle Introduction to Graph Neural Networks (Basics, DeepWalk, and GraphSage)
- A Gentle Introduction to Graph Neural Networks (Basics, DeepWalk, and GraphSage)
- A Gentle Introduction to Graph Neural Networks (Basics, DeepWalk, and GraphSage)
- A Gentle Introduction to Graph Neural Networks (Basics, DeepWalk, and GraphSage)
- A Gentle Introduction to Graph Neural Networks (Basics, DeepWalk, and GraphSage)
- A Gentle Introduction to Graph Neural Networks (Basics, DeepWalk, and GraphSage)
- A Gentle Introduction to Graph Neural Networks (Basics, DeepWalk, and GraphSage)
- Machine Learning for Recommender systems from Recombee
- A Gentle Introduction to Graph Neural Networks (Basics, DeepWalk, and GraphSage)
- PinSage: A new graph convolutional neural network for web-scale recommender systems
- Model-Based Machine Learning and Making Recommendations
- How Does Spotify Know You So Well?
- A Gentle Introduction to Graph Neural Networks (Basics, DeepWalk, and GraphSage)
- A Gentle Introduction to Graph Neural Networks (Basics, DeepWalk, and GraphSage)
- A Gentle Introduction to Graph Neural Networks (Basics, DeepWalk, and GraphSage)
- A Gentle Introduction to Graph Neural Networks (Basics, DeepWalk, and GraphSage)
- A Gentle Introduction to Graph Neural Networks (Basics, DeepWalk, and GraphSage)
- A Gentle Introduction to Graph Neural Networks (Basics, DeepWalk, and GraphSage)
- A Gentle Introduction to Graph Neural Networks (Basics, DeepWalk, and GraphSage)
- A Gentle Introduction to Graph Neural Networks (Basics, DeepWalk, and GraphSage)
- A Gentle Introduction to Graph Neural Networks (Basics, DeepWalk, and GraphSage)
- A Gentle Introduction to Graph Neural Networks (Basics, DeepWalk, and GraphSage)
- A Gentle Introduction to Graph Neural Networks (Basics, DeepWalk, and GraphSage)
- A Gentle Introduction to Graph Neural Networks (Basics, DeepWalk, and GraphSage)
- A Gentle Introduction to Graph Neural Networks (Basics, DeepWalk, and GraphSage)
- A Gentle Introduction to Graph Neural Networks (Basics, DeepWalk, and GraphSage)
- A Gentle Introduction to Graph Neural Networks (Basics, DeepWalk, and GraphSage)
- A Gentle Introduction to Graph Neural Networks (Basics, DeepWalk, and GraphSage)
- A Gentle Introduction to Graph Neural Networks (Basics, DeepWalk, and GraphSage)
- A Gentle Introduction to Graph Neural Networks (Basics, DeepWalk, and GraphSage)
- A Gentle Introduction to Graph Neural Networks (Basics, DeepWalk, and GraphSage)
- A Gentle Introduction to Graph Neural Networks (Basics, DeepWalk, and GraphSage)
- A Gentle Introduction to Graph Neural Networks (Basics, DeepWalk, and GraphSage)
- A Gentle Introduction to Graph Neural Networks (Basics, DeepWalk, and GraphSage)
- A Gentle Introduction to Graph Neural Networks (Basics, DeepWalk, and GraphSage)
- A Gentle Introduction to Graph Neural Networks (Basics, DeepWalk, and GraphSage)
- A Gentle Introduction to Graph Neural Networks (Basics, DeepWalk, and GraphSage)
- A Gentle Introduction to Graph Neural Networks (Basics, DeepWalk, and GraphSage)
- A Gentle Introduction to Graph Neural Networks (Basics, DeepWalk, and GraphSage)
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TensorFlow Implementations
- Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering
- Semi-Supervised Classification with Graph Convolutional Networks
- GraphSAGE
- Large-Scale Learnable Graph Convolutional Networks
- RippleNet
- MKR (multi-task learning for knowledge graph enhanced recommendation)
- DeepRec
- OpenRec
- Graph Attention Networks
- Variational Graph Auto-Encoder
- Deep Recursive Network Embedding with Regular Equivalence
- DeepWalk
- GraphRNN: Generating Realistic Graphs with Deep Auto-regressive Model
- Diffusion Convolutional Recurrent Neural Network
- Spatio-Temporal Graph Convolutional Networks
- Adversarially Regularized Graph Autoencoder
- Colab Notebook For Graph Nets and Item Connections / Recommendations
- Graph Nets in TensorFlow by DeepMind
- Adversarially Regularized Graph Autoencoder
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Research Papers
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Models
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Applications
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Relational Representation Learning
- Variational learning across domains with triplet information
- Link Prediction in Dynamic Graphs for Recommendation
- Multi-Task Graph Autoencoders
- On the Complexity of Exploration in Goal-driven Navigation - Shedivat, Lisa Lee, Ruslan Salakhutdinov, Eric Xing
- Deep Graph Infomax
- Image-Level Attentional Context Modeling Using Nested-Graph Neural Networks - Philippe Thiran, Maria Gabrani
- Compositional Language Understanding with Text-based Relational Reasoning
- Learning Graph Representation via Formal Concept Analysis
- A Simple Baseline Algorithm for Graph Classification
- Pitfalls of Graph Neural Network Evaluation
- TNE: A Latent Model for Representation Learning on Networks
- A Case for Object Compositionality in GANs
- Learning DPPs by Sampling Inferred Negatives
- LanczosNet: Multi-Scale Deep Graph Convolutional Networks
- Chess2vec: Learning Vector Representations for Chess
- Sparse Logistic Regression Learns All Discrete Pairwise Graphical Models
- Towards Sparse Hierarchical Graph Classifiers
- GRevnet: Improving Graph Neural Nets with Reversible Computation
- Detecting the Coarse Geometry of Networks
- Modeling Attention Flow on Graphs
- A Simple Baseline Algorithm for Graph Classification
- Learning Generative Models across Incomparable Spaces - Melis, Andreas Krause , Stefanie Jegelka **Best Paper Award**
- Hierarchical Bipartite Graph Convolution Networks
- Non-local RoI for Cross-Object Perception - Yao Tseng, Hwann-Tzong Chen, Shao-Heng Tai, Tyng-Luh Liu
- Node Attribute Prediction: An Evaluation of Within- versus Across-Network Tasks
- Implicit Maximum Likelihood Estimation
- Variational learning across domains with triplet information
- Fast k-Nearest Neighbour Search via Prioritized DCI
- Deep Determinantal Point Processes
- Higher-Order Graph Convolutional Layer - El-Haija, Bryan Perozzi, Amol Kapoor, Nazanin Alipourfard, Hrayr Harutyunyan
- Convolutional Set Matching for Graph Similarity
- Improving Generalization for Abstract Reasoning Tasks Using Disentangled Feature Representations
- From Node Embedding to Graph Embedding: Scalable Global Graph Kernel via Random Features - Hsu Yen, Kun Xu, Liang Zhao, Yinglong Xia, Michael Witbrock
- A Neural Framework for Learning DAG to DAG Translation
- Semi-supervised learning for clusterable graph embeddings with NMF
- Lifted Inference for Faster Training in end-to-end neural-CRF models
- Link Prediction in Dynamic Graphs for Recommendation
- Multi-Task Graph Autoencoders
- Personalized Neural Embeddings for Collaborative Filtering with Text
- Symbolic Relation Networks for Reinforcement Learning
- Extending the Capacity of CVAE for Face Sythesis and Modeling
- SARN: Relational Reasoning through Sequential Attention
- Pairwise Relational Networks using Local Appearance Features for Face Recognition - Nam Kang, YongHyun Kim, Daijin Kim
- Compositional Fairness Constraints for Graph Embeddings
- Improved Addressing in the Differentiable Neural Computer
- Efficient Unsupervised Word Sense Induction, Disambiguation and Embedding
- Importance of object selection in Relational Reasoning tasks
- On Robust Learning of Ising Models
- Feed-Forward Neural Networks need Inductive Bias to Learn Equality Relations
- Tensor Random Projection for Low Memory Dimension Reduction
- Leveraging Representation and Inference through Deep Relational Learning
- Learning Embeddings for Approximate Lifted Inference in MLNs
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Survey papers
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Videos
- Intro to Graph Convolutional Networks
- Graph Convolutional Networks for Node Classification
- Jure Leskovec - Large-scale Graph Representation Learning
- Attention in Neural Networks
- Michael Bronstein - Geometric deep learning on graphs: going beyond Euclidean data
- Yann LeCun - Graph Embedding, Content Understanding, and Self-Supervised Learning
- DeepWalk: Turning Graphs Into Features via Network Embeddings with Neo4j
- What is a Random Walk?
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Public Datasets
- Recommender Systems Datasets
- GroupLens
- MovieLens
- HetRec2011
- WikiLens
- Book-Crossing
- Jester
- EachMovie
- Amazon Product Data
- SNAP Datasets
- #nowplaying Dataset
- Last.fm Datasets
- Million Song Dataset
- Frappe
- Yahoo! Webscope Program
- Yelp Dataset Challenge
- Foursquare
- Epinions
- Google Local
- LibimSeTi
- Scholarly Paper Recommendation Datasets
- Netflix Prize Data Set
- FilmTrust,CiaoDVD
- Chicago Entree
- Douban
- BibSonomy
- Delicious
- MACLab LJ Datasets
- Steam Video Games
- Anime Recommendations Database
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Recommendation Algorithms
- Wikipedia
- Wikipedia
- Matrix Factorization: A Simple Tutorial and Implementation in Python
- Matrix Factorization Techiques for Recommendaion Systems
- Wikipedia
- Factorization Meets the Neighborhood: a Multifaceted Collaborative Filtering Model
- Probabilistic Matrix Factorization
- Collaborative Filtering for Implicit Feedback Datasets
- Factorization Machines
- SLIM: Sparse Linear Methods for Top-N Recommender Systems
- Global and Local SLIM
- Wikipedia
- WSABIE: Scaling Up To Large Vocabulary Image Annotation
- Top-1 Feedback
- k-order statistic loss
- Deep content-based music recommendation
- DropoutNet: Addressing Cold Start in Recommender Systems
- Item2vec
- Deep Neural Networks for YouTube Recommendations
- Deep Learning based Recommender System: A Survey and New Perspectives
- TensorFlow Wide & Deep Learning
- Collaborative Memory Network for Recommendation Systems
- Collaborative Deep Learning for Recommender Systems
Programming Languages
Categories
Keywords
deep-learning
4
recommender-systems
3
tensorflow
3
recommendation-system
3
python
3
deep-neural-networks
2
graphs
2
knowledge-graph
2
neural-networks
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recommendation
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ml
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machine-learning
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top-n-recommendations
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rating-prediction
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neural-network
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matrix-factorization
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factorization-machine
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collaborative-filtering
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multi-task-learning
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graph-signal-processing
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graph-neural-networks
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convolutional-neural-networks
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sonnet
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graph-networks
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artificial-intelligence
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traffic-data
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time-series
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spatiotemporal-forecasting
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iclr2018
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deep-learning-graphs
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rating
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prediction
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graph-propagation-algorithm
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graph-embedding
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graph
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deepwalk
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network-representation-learning
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network-embedding
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centrality
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self-attention
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graph-attention-networks
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attention-mechanism
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recommendation-algorithm
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