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Weekly reading group on Graphs at Mila

Weekly Reading Group on Graphs at Mila

Organizer: Shagun Sodhani


Date Topic Presenters Slides
23rd April, 2019 End of term    
16th April, 2019 Continuous-Time Dynamic Network Embeddings Weiping Song Slides
9th April, 2019 Improved Knowledge Graph Embedding using Background Taxonomic Information Bahare Fatemi Slides
2nd April, 2019 Drug Discovery and GNNs Sun Fanyun Slides
19th March, 2019 GNN Explainer: A Tool for Post-hoc Explanation of Graph Neural Networks Shagun Sodhani Slides
12th March, 2019 Combining Graph Neural Networks with Statistical Relational Learning Meng Qu Slides
5th March, 2019 Spring Break    
26th February, 2019 RotatE: Knowledge Graph Embedding by Relational Rotation in Complex Space Jian Tang Slides
19th February, 2019 GraphVite Zhaocheng Zhu Slides
12th February, 2019 Multi-GCN: Graph Convolutional Networks for Multi-View Networks, with Applications to Global Poverty Simon Blackburn Slides
5th February, 2019 A review of semi-supervised learning on graphs using graph convolutional networks Carlos Eduardo Lassance Slides
29th January, 2019 Compositional Fairness Constraints for Graph Embeddings Joey Bose Slides
22nd January, 2019 Happy ICML    
15th January, 2019 Knowledge Vault: A Web-Scale Approach to Probabilistic Knowledge Fusion Disha Shrivastava Slides


Date Topic Presenters Slides
22nd November, 2018 End of Semester    
15th November, 2018 Towards Sparse Hierarchical Graph Classifiers Cătălina Cangea Slides
8th November, 2018 Cancelled    
1st November, 2018 Multi-hop Reasoning with Graph Convolutional Networks Carlos Eduardo Lassance Slides
25th October, 2018 Diffusion-Based Approximate Value Functions Martin Klissarov Slides
18th October, 2018 GraphDial Prasanna Parthasarathi WIP
11th October, 2018 Learning Graphical State Transitions Daniel D. Johnson Slides
4th October, 2018 Hyperbolic Graph Embeddings William L. Hamilton Slides
27th September, 2018 Deep Graph Informax Petar Veličković Slides
20th September, 2018 Graph Convolutional Neural Networks for Web-Scale Recommender Systems Cătălina Cangea Slides
13th September, 2018 Latent Molecular Optimization for Targeted Therapeutic Design Andreea Deac Slides
29th August, 2018 Go for a Walk and Arrive at the Answer: Reasoning Over Paths in Knowledge Bases using Reinforcement Learning Zhiqing Sun Slides
22nd August, 2018 A simple neural network module for relational reasoning, Relational recurrent neural networks, Relational deep reinforcement learning Petar Veličković Slides
15th August, 2018 NerveNet: Learning Structured Policy with Graph Neural Networks Cătălina Cangea Slides
8th August, 2018 A Graph-to-Sequence Model for AMR-to-Text Generation Koustuv Sinha Slides
1st August, 2018 NetGAN: Generating Graphs via Random Walk Cheng Yang Slides
25th July, 2018 Neural Relational Inference for Interacting Systems Petar Velickovic Slides
18th July, 2018 Hierarchical Graph Representation Learning with Differentiable Pooling Simon Blackburn Slides
11th July, 2018 ICML    
4th July, 2018 Graph Convolutional Policy Network for Goal-Directed Molecular Graph Generation Andreea Deac Slides
27th June, 2018 Adversarial Attack on Graph Structured Data Cheng Yang Slides
20th June, 2018 Representation Learning on Graphs with Jumping Knowledge Networks Shagun Sodhani Slides
13th June, 2018 Stochastic Training of Graph Convolutional Networks with Variance Reduction Shagun Sodhani Slides
6th June, 2018 GraphVAE: Towards Generation of Small Graphs Using Variational Autoencoders Alejandro Posada Slides
30th May, 2018 Towards Gene Expression Convolutions using Gene Interaction Graphs Joseph Cohen Slides
23rd May, 2018 Automatically Extracting Action Graphs from Materials Science Synthesis Procedures Francis and Karam Slides
16th May, 2018 NIPS!    
9th May, 2018 GraphRNN: A Deep Generative Model for Graphs Shagun Sodhani Slides
2nd May, 2018 Happy ICLR!    
25th April, 2018 Junction Tree Variational Autoencoder for Molecular Graph Generation Yu-Hsiang Huang slides
18th April, 2018 Crystal Graph Convolutional Neural Networks for an Accurate and Interpretable Prediction of Material Properties Simon Blackburn slides
11th April, 2018 Graph Representation and Molecular Property Prediction using Message Passing Neural Networks Jian Tang, Karam Thomas, Shagun Sodhani slides