2022 ICLR 关于图的接收列表
2022 ICLR 可以参考 《ICLR 2022图学习领域都在研究什么?Open Review投稿文章一览》
Graph Condensation for Graph Neural Networks
Graph Neural Networks with Learnable Structural and Positional Representations
Semi-relaxed Gromov-Wasserstein divergence and applications on graphs
EXACT: Scalable Graph Neural Networks Training via Extreme Activation Compression
How Attentive are Graph Attention Networks?
Handling Distribution Shifts on Graphs: An Invariance Perspective
Discovering Invariant Rationales for Graph Neural Networks
End-to-End Learning of Probabilistic Hierarchies on Graphs
Convergent Graph Solvers
Graphon based Clustering and Testing of Networks: Algorithms and Theory
Neural Link Prediction with Walk Pooling
PF-GNN: Differentiable particle filtering based approximation of universal graph representations
Top-N: Equivariant Set and Graph Generation without Exchangeability
NodePiece: Compositional and Parameter-Efficient Representations of Large Knowledge Graphs
Topological Graph Neural Networks
Towards Training Billion Parameter Graph Neural Networks for Atomic Simulations
Automated Self-Supervised Learning for Graphs
Query Embedding on Hyper-Relational Knowledge Graphs
PipeGCN: Efficient Full-Graph Training of Graph Convolutional Networks with Pipelined Feature Communication
Equivariant and Stable Positional Encoding for More Powerful Graph Neural Networks
Neural Methods for Logical Reasoning over Knowledge Graphs
Graph-Relational Domain Adaptation
IGLU: Efficient GCN Training via Lazy Updates
Cold Brew: Distilling Graph Node Representations with Incomplete or Missing Neighborhoods
Graph Auto-Encoder via Neighborhood Wasserstein Reconstruction
Large-Scale Representation Learning on Graphs via Bootstrapping
Graph-Guided Network for Irregularly Sampled Multivariate Time Series
Is Homophily a Necessity for Graph Neural Networks?
From Stars to Subgraphs: Uplifting Any GNN with Local Structure Awareness
Learn Locally, Correct Globally: A Distributed Algorithm for Training Graph Neural Networks
Efficient Neural Causal Discovery without Acyclicity Constraints
Space-Time Graph Neural Networks
GRAND++: Graph Neural Diffusion with A Source Term
Learning to Schedule Learning rate with Graph Neural Networks
LEARNING GUARANTEES FOR GRAPH CONVOLUTIONAL NETWORKS ON THE STOCHASTIC BLOCK MODEL
Understanding and Improving Graph Injection Attack by Promoting Unnoticeability
Information Gain Propagation: a New Way to Graph Active Learning with Soft Labels
Self-Supervised Graph Neural Networks for Improved Electroencephalographic Seizure Analysis
Pre-training Molecular Graph Representation with 3D Geometry
Node Feature Extraction by Self-Supervised Multi-scale Neighborhood Prediction
Graph-based Nearest Neighbor Search in Hyperbolic Spaces
On Evaluation Metrics for Graph Generative Models
Spatial Graph Attention and Curiosity-driven Policy for Antiviral Drug Discovery
Graph Neural Network Guided Local Search for the Traveling Salesperson Problem
Graph-less Neural Networks: Teaching Old MLPs New Tricks Via Distillation
Spherical Message Passing for 3D Molecular Graphs
Why Propagate Alone? Parallel Use of Labels and Features on Graphs
Filling the G_ap_s: Multivariate Time Series Imputation by Graph Neural Networks
Do We Need Anisotropic Graph Neural Networks?
Explainable GNN-Based Models over Knowledge Graphs
Neural graphical modelling in continuous-time: consistency guarantees and algorithms
DEGREE: Decomposition Based Explanation for Graph Neural Networks
Predicting Physics in Mesh-reduced Space with Temporal Attention
Inductive Relation Prediction Using Analogy Subgraph Embeddings
Simple GNN Regularisation for 3D Molecular Property Prediction and Beyond
Neural Relational Inference with Node-Specific Information
Granger causal inference on DAGs identifies genomic loci regulating transcription
Ada-NETS: Face Clustering via Adaptive Neighbour Discovery in the Structure Space
Chemical-Reaction-Aware Molecule Representation Learning
Equivariant Graph Mechanics Networks with Constraints
Towards Deepening Graph Neural Networks: A GNTK-based Optimization Perspective
Delaunay Component Analysis for Evaluation of Data Representations
Triangle and Four Cycle Counting with Predictions in Graph Streams
OntoProtein: Protein Pretraining With Gene Ontology Embedding
Learning to Extend Molecular Scaffolds with Structural Motifs
Neural Models for Output-Space Invariance in Combinatorial Problems
What’s Wrong with Deep Learning in Tree Search for Combinatorial Optimization
GNN is a Counter? Revisiting GNN for Question Answering
Fairness Guarantees under Demographic Shift
Retriever: Learning Content-Style Representation as a Token-Level Bipartite Graph
Back2Future: Leveraging Backfill Dynamics for Improving Real-time Predictions in Future
On the Learning and Learnability of Quasimetrics
Using Graph Representation Learning with Schema Encoders to Measure the Severity of Depressive Symptoms
Relational Learning with Variational Bayes
A Biologically Interpretable Graph Convolutional Network to Link Genetic Risk Pathways and Imaging Phenotypes of Disease
Hidden Parameter Recurrent State Space Models For Changing Dynamics Scenarios
Learning Graphon Mean Field Games and Approximate Nash Equilibria
Topological Experience Replay
Differentiable Scaffolding Tree for Molecule Optimization
Structure-Aware Transformer Policy for Inhomogeneous Multi-Task Reinforcement Learning
MoReL: Multi-omics Relational Learning
Geometric Transformers for Protein Interface Contact Prediction
EigenGame Unloaded: When playing games is better than optimizing
GLASS: GNN with Labeling Tricks for Subgraph Representation Learning
C-Planning: An Automatic Curriculum for Learning Goal-Reaching Tasks
An Autoregressive Flow Model for 3D Molecular Geometry Generation from Scratch
R4D: Utilizing Reference Objects for Long-Range Distance Estimation
Learning 3D Representations of Molecular Chirality with Invariance to Bond Rotations
Learning to Remember Patterns: Pattern Matching Memory Networks for Traffic Forecasting
Non-Parallel Text Style Transfer with Self-Parallel Supervision
You are AllSet: A Multiset Function Framework for Hypergraph Neural Networks
Know Your Action Set: Learning Action Relations for Reinforcement Learning
Crystal Diffusion Variational Autoencoder for Periodic Material Generation
GraphENS: Neighbor-Aware Ego Network Synthesis for Class-Imbalanced Node Classification
Learning Object-Oriented Dynamics for Planning from Text
Learning Scenario Representation for Solving Two-stage Stochastic Integer Programs
Adversarial Robustness Through the Lens of Causality
Rethinking Network Design and Local Geometry in Point Cloud: A Simple Residual MLP Framework
Generalized Demographic Parity for Group Fairness
Contextualized Scene Imagination for Generative Commonsense Reasoning
Vitruvion: A Generative Model of Parametric CAD Sketches
Closed-form Sample Probing for Learning Generative Models in Zero-shot Learning
Topologically Regularized Data Embeddings
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