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