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