neurips_graphs_accepted.txt

Strongly Incremental Constituency Parsing with Graph Neural Networks
Adversarial Attack on Graph Neural Networks with Limited Node Access
On the equivalence of molecular graph convolution and molecular wave function with poor basis set
Generative 3D Part Assembly via Dynamic Graph Learning
Neural Message Passing for Multi-Relational Ordered and Recursive Hypergraphs
Evolving Graphical Planner: Contextual Global Planning for Vision-and-Language Navigation
Can Q-Learning with Graph Networks Learn a Generalizable Branching Heuristic for a SAT Solver?
Graph Cross Networks with Vertex Infomax Pooling
Open Graph Benchmark: Datasets for Machine Learning on Graphs
Cross-scale Internal Graph Convolution Network for Image Super-Resolution
Learning to Extrapolate Knowledge: Transductive Few-shot Out-of-Graph Link Prediction
Graduated Assignment for Joint Multi-Graph Matching and Clustering with Application to Unsupervised Graph Matching Network Learning
Provable Overlapping Community Detection in Weighted Graphs
GPS-Net: Graph-based Photometric Stereo Network
A graph similarity for deep learning
Path Integral Based Convolution and Pooling for Graph Neural Networks
Domain Adaptation as a Problem of Inference on Graphical Models
Stochastic Deep Gaussian Processes over Graphs
Scalable Graph Neural Networks via Bidirectional Propagation
GROVER: Self-Supervised Message Passing Transformer on Large-scale Molecular Graphs
Duality-Induced Regularizer for Tensor Factorization Based Knowledge Graph Completion
Set2Graph: Learning Graphs From Sets
Multipole Graph Neural Operator for Parametric Partial Differential Equations
Parameterized Explainer for Graph Neural Network
Random Walk Graph Neural Networks
Dirichlet Graph Variational Autoencoder
Natural Graph Networks
Optimization and Generalization Analysis of Transduction through Gradient Boosting and Application to Multi-scale Graph Neural Networks
Fast Epigraphical Projection-based Incremental Algorithms for Wasserstein Distributionally Robust Support Vector Machine
Weisfeiler and Leman go sparse: Towards scalable higher-order graph embeddings
Unsupervised Joint k-node Graph Representations with Compositional Energy-Based Models
Efficient Algorithms for Device Placement of DNN Graph Operators
PGM-Explainer: Probabilistic Graphical Model Explanations for Graph Neural Networks
Sparse Graphical Memory for Robust Planning
Implicit Graph Neural Networks
GNNGuard: Defending Graph Neural Networks against Adversarial Attacks
Towards Deeper Graph Neural Networks with Differentiable Group Normalization
COPT: Coordinated Optimal Transport on Graphs
Less is More: A Deep Graph Metric Learning Perspective Using Few Proxies
Probabilistic Circuits for Variational Inference in Discrete Graphical Models
Searching Recurrent Architecture for Path-based Knowledge Graph Embedding
Universal Function Approximation on Graphs
CASTLE: Regularization via Auxiliary Causal Graph Discovery
Deep Relational Topic Modeling via Graph Poisson Gamma Belief Network
Towards Scale-Invariant Graph-related Problem Solving by Iterative Homogeneous GNNs
Graph Stochastic Neural Networks for Semi-supervised Learning
How hard is to distinguish graphs with graph neural networks?
Community detection in sparse time-evolving graphs with a dynamical Bethe-Hessian
Language and Visual Entity Relationship Graph for Agent Navigation
Graph Random Neural Networks for Semi-Supervised Learning on Graphs
Robust Multi-Object Matching via Iterative Reweighting of the Graph Connection Laplacian
Digraph Inception Convolutional Networks
Learning of Discrete Graphical Models with Neural Networks
Graph Meta Learning via Local Subgraphs
Dense Correspondences between Human Bodies via Learning Transformation Synchronization on Graphs
Building powerful and equivariant graph neural networks with message-passing
Reinforcement Learning with Feedback Graphs
Can Graph Neural Networks Count Substructures?
Manifold structure in graph embeddings
Attribution for Graph Neural Networks
Convergence and Stability of Graph Convolutional Networks on Large Random Graphs
Learning Graph Structure with A Finite-State Automaton Layer
Learning Dynamic Belief Graphs to Generalize on Text-Based Games
Principal Neighbourhood Aggregation for Graph Nets
Graphon Neural Networks and the Transferability of Graph Neural Networks
Factorizable Graph Convolutional Networks
Handling Missing Data with Graph Representation Learning
EvolveGraph: Multi-Agent Trajectory Prediction with Dynamic Relational Reasoning
Distance Encoding -- Design Provably More Powerful GNNs for Structural Representation Learning
Design Space for Graph Neural Networks
Pointer Graph Networks
Learning Physical Graph Representations from Visual Scenes
Reward Propagation Using Graph Convolutional Networks
Learning Some Popular Gaussian Graphical Models without Condition Number Bounds
Subgraph Neural Networks
Strongly local p-norm-cut algorithms for semi-supervised learning and local graph clustering
Beyond Homophily in Graph Neural Networks: Current Limitations and Effective Designs
Efficient Learning of Discrete Graphical Models
Adaptive Graph Convolutional Recurrent Network for Traffic Forecasting
Uncertainty Aware Semi-Supervised Learning on Graph Data
Learning to Execute Programs with Instruction Pointer Attention Graph Neural Networks
Beta Embeddings for Multi-Hop Logical Reasoning in Knowledge Graphs
Learning to Decode: Reinforcement Learning for Decoding of Sparse Graph-Based Channel Codes
Scattering GCN: Overcoming Oversmoothness in Graph Convolutional Networks
GCOMB: Learning Budget-constrained Combinatorial Algorithms over Billion-sized Graphs
Pre-Training Graph Neural Networks: A Contrastive Learning Framework with Augmentations
Variational Inference for Graph Convolutional Networks in the Absence of Graph Data and Adversarial Settings
Certified Robustness of Graph Convolution Networks for Graph Classification under Topological Attacks
Node Classification on Graphs with Few-Shot Novel Labels via Meta Transformed Network Embedding
A Novel Approach for Constrained Optimization in Graphical Models
Adversarially-learned Inference via an Ensemble of Discrete Undirected Graphical Models
Nonconvex Sparse Graph Learning under Laplacian-structured Graphical Model
DeepSVG: A Hierarchical Generative Network for Vector Graphics Animation
Self-supervised Auxiliary Learning with Meta-paths for Heterogeneous Graphs
Binary Matrix Completion with Hierarchical Graph Side Information
Graph Geometry Interaction Learning
Fairness without Demographics through Adversarially Reweighted Learning
Bandit Samplers for Training Graph Neural Networks
On the Power of Louvain for Graph Clustering
Multimodal Graph Networks for Compositional Generalization in Visual Question Answering
Erdos Goes Neural: an Unsupervised Learning Framework for Combinatorial Optimization on Graphs
Factor Graph Neural Networks
Graph Policy Network for Transferable Active Learning on Graphs
DiffGCN: Graph Convolutional Networks via Differential Operators and Algebraic Multigrid Pooling
Spectral Temporal Graph Neural Network for Multivariate Time-series Forecasting
Curvature Regularization to Prevent Distortion in Graph Embedding
A polynomial-time algorithm for learning nonparametric causal graphs
Generalized Independent Noise Condition for Estimating Linear Non-Gaussian Latent Variable Graphs
AI Feynman 2.0: Pareto-optimal symbolic regression exploiting graph modularity
Universal Steganography and Watermarking: Towards Understanding and Utilizing Deep Hiding
Higher-Order Spectral Clustering of Directed Graphs
Reliable Graph Neural Networks via Robust Location Estimation
Iterative Deep Graph Learning for Graph NeuralNetworks: Better and Robust Node Embeddings
Deep Graph Pose: a semi-supervised deep graphical model for improved animal pose tracking
Towards practical differentially private causal graph discovery
Neural Topographic Factor Analysis for fMRI Data
Provable, Scalable and Automatic Perturbation Analysis on General Computational Graphs
Adaptive Shrinkage Estimation for Streaming Graphs
Graph Information Bottleneck
Adversarial Attacks on Deep Graph Matching
Factor Graph Grammars
Rethinking pooling in graph neural networks
Transferable Graph Optimizers for ML Compilers