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Graph Neural Networks

4,522 papers

Papers per year

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Papers

Bandit Samplers for Training Graph Neural Networks NIPS 2020
Graph Geometry Interaction Learning NIPS 2020
Beyond Homophily in Graph Neural Networks: Current Limitations and Effective Designs NIPS 2020
Deep Statistical Solvers NIPS 2020
Subgraph Neural Networks NIPS 2020
Rotation-Invariant Local-to-Global Representation Learning for 3D Point Cloud NIPS 2020
Certified Robustness of Graph Convolution Networks for Graph Classification under Topological Attacks NIPS 2020
Learning to Execute Programs with Instruction Pointer Attention Graph Neural Networks NIPS 2020
Refactoring Policy for Compositional Generalizability using Self-Supervised Object Proposals NIPS 2020
Fully Convolutional Mesh Autoencoder using Efficient Spatially Varying Kernels NIPS 2020
GNNGuard: Defending Graph Neural Networks against Adversarial Attacks NIPS 2020
Self-supervised Auxiliary Learning with Meta-paths for Heterogeneous Graphs NIPS 2020
GPS-Net: Graph-based Photometric Stereo Network NIPS 2020
Can Graph Neural Networks Count Substructures? NIPS 2020
BRP-NAS: Prediction-based NAS using GCNs NIPS 2020
JAX MD: A Framework for Differentiable Physics NIPS 2020
Implicit Graph Neural Networks NIPS 2020
PGM-Explainer: Probabilistic Graphical Model Explanations for Graph Neural Networks NIPS 2020
Self-Supervised Graph Transformer on Large-Scale Molecular Data NIPS 2020
Uncertainty Aware Semi-Supervised Learning on Graph Data NIPS 2020
Principal Neighbourhood Aggregation for Graph Nets NIPS 2020
Reliable Graph Neural Networks via Robust Aggregation NIPS 2020
Graph Cross Networks with Vertex Infomax Pooling NIPS 2020
Building powerful and equivariant graph neural networks with structural message-passing NIPS 2020
Scattering GCN: Overcoming Oversmoothness in Graph Convolutional Networks NIPS 2020