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GNNs in NeurIPS 2019

Sunday (Expo day)

  • Demo: AliGraph link
  • Workshop: Alibaba Group link

Monday (workshop and tutorial)

title topic session
Edge Contraction Pooling for Graph Neural Networks graph pooling NewInML
Popularity Agnostic Evaluation of Knowledge Graph Embeddings knowledge graph NewInML
Triplet-Aware Scene Graph Embeddings graph embedding WiML
Applying Graph Neural Networks on Multimodal Biological Data GNN WiML
Graph combinatorics based group-level network inference with an application to brain connectome study graph embedding WiML
Predictive Temporal Embedding of Dynamic Graphs graph embedding WiML
Knowledge Hypergraphs: Extending Knowledge Graphs Beyond Binary Relations knowledge graph WiML
Construction of knowledge graphs from Spanish text using Linked Data knowledge graph WiML
Community Detection with Graph Convolutional Networks using Semi-supervised Node Classification GCN WiML
Robust representations for transfer learning on heterogeneous spatial graphs Chidubem Iddianozie spatial graph BAI
Machine Learning for Computational Biology and Health general Tutorial

Tuesday (main track)

Posters

title session poster
Certifiable Robustness to Graph Perturbations adversarial learning link
Spectral Modification of Graphs for Improved Spectral Clustering clustering link
Beyond Vector Spaces: Compact Data Representation as Differentiable Weighted Graphs representation learning link
Provably Powerful Graph Networks representation learning link
Quaternion Knowledge Graph Embeddings representation learning link
Efficiently Estimating Erdos-Renyi Graphs with Node Differential Privacy privacy link
GNNExplainer: Generating Explanations for Graph Neural Networks deep learning link
Efficient Graph Generation with Graph Recurrent Attention Networks generative model link
PasteGAN: A Semi-Parametric Method to Generate Image from Scene Graph generative model link
Exact Combinatorial Optimization with Graph Convolutional Neural Networks combinatorial optimization link
D-VAE: A Variational Autoencoder for Directed Acyclic Graphs AutoML link
Learning to Propagate for Graph Meta-Learning meta learning link
Retrosynthesis Prediction with Conditional Graph Logic Network structure prediction link
Universal Invariant and Equivariant Graph Neural Networks approximation link

Wednesday (main track)

Posters

title session poster
Heterogeneous Graph Learning for Visual Commonsense Reasoning representation learning link spotlight
A Unified Framework for Data Poisoning Attack to Graph-based Semi-supervised Learning adverarial learning link
Break the Ceiling: Stronger Multi-scale Deep Graph Convolutional Networks semi-supervised learning link
Generalized Matrix Means for Semi-Supervised Learning with Multilayer Graphs semi-supervised learning link
Graph Agreement Models for Semi-Supervised Learning semi-supervised learning link
Graph-Based Semi-Supervised Learning with Non-ignorable Non-response semi-supervised learning link
HyperGCN: A New Method For Training Graph Convolutional Networks on Hypergraphs semi-supervised learning link
Graph Normalizing Flows generative model link
Hyper-Graph-Network Decoders for Block Codes belief propagation link
Structured Graph Learning Via Laplacian Spectral Constraints graphical model link
Guided Similarity Separation for Image Retrieval representation learning link Oral
Diffusion Improves Graph Learning relational learning link
A Flexible Generative Framework for Graph-based Semi-supervised Learning relational learning link
Online Prediction of Switching Graph Labelings with Cluster Specialists online learning link
Graph Neural Tangent Kernel: Fusing Graph Neural Networks with Graph Kernels relational learning link
Hyperbolic Graph Convolutional Neural Networks relational learning link
Hyperbolic Graph Neural Networks relational learning link
Multi-relational Poincaré Graph Embeddings relational learning link
On the equivalence between graph isomorphism testing and function approximation with GNNs relational learning link
A Unifying Framework for Spectrum-Preserving Graph Sparsification and Coarsening spectral methods link
Revisiting the Bethe-Hessian: Improved Community Detection in Sparse Heterogeneous Graphs spepctral methods link
Understanding Attention and Generalization in Graph Neural Networks attention model link
Semi-Implicit Graph Variational Auto-Encoders variational inference link

Thursday (main track)

Posters

title session poster
Layer-Dependent Importance Sampling for Training Deep and Large Graph Convolutional Networks representation learning link
Learning Transferable Graph Exploration application link
KerGM: Kernelized Graph Matching kernel method link spotlight
N-Gram Graph: Simple Unsupervised Representation for Graphs, with Applications to Molecules representation learning link spotlight
Rethinking Kernel Methods for Node Representation Learning on Graphs kernel method link
Graph Transformer Networks representation learning link
Understanding the Representation Power of Graph Neural Networks in Learning Graph Topology representation learning link
Exploring Algorithmic Fairness in Robust Graph Covering Problem fairness link
Devign: Effective Vulnerability Identification by Learning Comprehensive Program Semantics via Graph Neural Networks privacy link
On Differentially Private Graph Sparsification and Applications privacy link
DFNets: Spectral CNNs for Graphs with Feedback-Looped Filters convolutional filter link
Layer-Dependent Importance Sampling for Training Deep and Large Graph Convolutional Networks representation learning link
Wasserstein Weisfeiler-Lehman Graph Kernels kernel method link spotlight
Learning metrics for persistence-based summaries and applications for graph classification kernel method link
Generative Models for Graph-Based Protein Design generative model link
Graph Structured Prediction Energy Networks structure prediction link
Conditional Structure Generation through Graph Variational Generative Adversarial Nets graph embedding link
GOT: An Optimal Transport framework for Graph comparison network analysis link
Variational Graph Recurrent Neural Networks network analysis link
vGraph: A Generative Model for Joint Community Detection and Node Representation Learning representation learning link
Learning Transferable Graph Exploration graph embedding link
Social-BiGAT: Multimodal Trajectory Forecasting using Bicycle-GAN and Graph Attention Networks generative model link
Recurrent Space-time Graph Neural Networks representation learning link
End to end learning and optimization on graphs combinatorial optimization link
DRUM: End-To-End Differentiable Rule Mining On Knowledge Graphs representation learning link

Friday (workshop)

Workshop Graph Representation Learning @ West Exhibition Hall A

Covered in other workshops

title topic workshop
Probabilistic End-to-End Graph-based Semi-Supervised Learning semi-supervised learning BDL
Entropic Graph Spectrum clustering ITML
Deep Clustering by Gaussian Mixture Variational Autoencoders with Graph Embedding clustering ITML
Graph Structured Prediction Energy Net Algorithms structure prediction PGR
Learning Optimization Models of Graphs optimization PGR
Structured differentiable models of 3D scenes via generative scene graphs generative model PGR
Populating Web Scale Knowledge Graphs using Distantly Supervised Relation Extraction and Validation knowledge graph KR2ML
Can Graph Neural Networks Help Logic Reasoning? knowledge graph KR2ML
Knowledge Graph-Driven Conversational Agents knowledge graph KR2ML
TransINT: Embedding Implication Rules in Knowledge Graphs with Isomorphic Intersections of Linear Subspaces knowledge graph KR2ML

Saturday (workshop)

title topic workshop
Generalization Bounds for Knowledge Graph Embedding (Trained by Maximum Likelihood) graph embedding ML with Guarantees
Functional Annotation of Human Cognitive States using Graph Convolution Networks representation learning Neuro AI workshop (contributed talk)
Learning Symbolic Physics with Graph Networks physics ML4Physics
SwarmNet: Towards Imitation Learning of Multi-Robot Behavior with Graph Neural Networks application robot-learning
A Knowledge Graph Based Health Assistant knowledge graph AISG
Zero-Shot Learning for Fast Optimization of Computation Graphs optimization ML for system
Multi-domain Dialogue State Tracking as Dynamic Knowledge Graph Enhanced Question Answering knowledge graph conversational AI
The Graph Hawkes Network for Reasoning on Temporal Knowledge Graphs knowledge graph TPP (oral)
Deep Hyperedges: a Framework for Transductive and Inductive Learning on Hypergraphs representation learning sets partitions
Finding densest subgraph in probabilistically evolving graphs structural learning sets partitions
Hypergraph Partitioning using Tensor Eigenvalue Decomposition structural learning sets partitions
Joint Interaction and Trajectory Prediction for Autonomous Driving using Graph Neural Networks application ML4AD
Efficient structure learning with automatic sparsity selection for causal graph processes causal inference causal ML
A Graph Autoencoder Approach to Causal Structure Learning structural learning causal ML

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License

CC0

To the extent possible under law, Hongwei Jin has waived all copyright and related or neighboring rights to this work.