Media Summary: Speaker: Jihyeong Jung, KAIST Authors: Jihyeong Jung, Sangwoo Seo, Sungwon Kim and Chanyoung Park. This is official ... This video records our presentation for our work published at In Proceedings of the International Conference on Machine

Icml 2024 Tutorial Graph Learning - Detailed Analysis & Overview

Speaker: Jihyeong Jung, KAIST Authors: Jihyeong Jung, Sangwoo Seo, Sungwon Kim and Chanyoung Park. This is official ... This video records our presentation for our work published at In Proceedings of the International Conference on Machine [ICML 2024] Mitigating Oversmoothing Through Reverse Process of GNNs for Heterophilic Graphs Project page (with further readings): Abstract: We divide "intelligence" into multiple dimensions (like ... [ICML 2024] Individual Fairness in Graph Decomposition

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ICML 2024 Tutorial -  Graph Learning: Principles, Challenges, and Open Directions
Triplet Graph Transformers: Advancing Molecular Graph Learning | ICML 2024 Poster Presentation
Introduction of ICML 2024  paper VisionGraph
ICML 2024 -  Unsupervised Episode Generation for Graph Meta-learning
2024 ICML How Universal Polynomial Bases Enhance Spectral Graph Neural Networks
ICML 2024 Tutorial"Machine Learning on Function spaces #NeuralOperators"
[ICML 2024] MathScale: Scaling Instruction Tuning for Mathematical Reasoning
[ICML 2024] Ensemble Pruning for Out-of-distribution Generalization
[ICML 2024] Mitigating Oversmoothing Through Reverse Process of GNNs for Heterophilic Graphs
ICML 2024 Tutorial: Physics of Language Models
Uncertainty for Active Learning on Graphs (ICML 2024)
ICML2024
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ICML 2024 Tutorial -  Graph Learning: Principles, Challenges, and Open Directions

ICML 2024 Tutorial - Graph Learning: Principles, Challenges, and Open Directions

Video for the

Triplet Graph Transformers: Advancing Molecular Graph Learning | ICML 2024 Poster Presentation

Triplet Graph Transformers: Advancing Molecular Graph Learning | ICML 2024 Poster Presentation

Paper: https://arxiv.org/abs/2402.04538 Discover how Triplet

Introduction of ICML 2024  paper VisionGraph

Introduction of ICML 2024 paper VisionGraph

Introduction of

ICML 2024 -  Unsupervised Episode Generation for Graph Meta-learning

ICML 2024 - Unsupervised Episode Generation for Graph Meta-learning

Speaker: Jihyeong Jung, KAIST Authors: Jihyeong Jung, Sangwoo Seo, Sungwon Kim and Chanyoung Park. This is official ...

2024 ICML How Universal Polynomial Bases Enhance Spectral Graph Neural Networks

2024 ICML How Universal Polynomial Bases Enhance Spectral Graph Neural Networks

This video records our presentation for our work published at

ICML 2024 Tutorial"Machine Learning on Function spaces #NeuralOperators"

ICML 2024 Tutorial"Machine Learning on Function spaces #NeuralOperators"

ICML 2024 Tutorial

[ICML 2024] MathScale: Scaling Instruction Tuning for Mathematical Reasoning

[ICML 2024] MathScale: Scaling Instruction Tuning for Mathematical Reasoning

Paper: https://huggingface.co/papers/2403.02884 Github: https://github.com/microsoft/unilm/tree/master/mathscale Large ...

[ICML 2024] Ensemble Pruning for Out-of-distribution Generalization

[ICML 2024] Ensemble Pruning for Out-of-distribution Generalization

In Proceedings of the International Conference on Machine

[ICML 2024] Mitigating Oversmoothing Through Reverse Process of GNNs for Heterophilic Graphs

[ICML 2024] Mitigating Oversmoothing Through Reverse Process of GNNs for Heterophilic Graphs

[ICML 2024] Mitigating Oversmoothing Through Reverse Process of GNNs for Heterophilic Graphs

ICML 2024 Tutorial: Physics of Language Models

ICML 2024 Tutorial: Physics of Language Models

Project page (with further readings): https://physics.allen-zhu.com/ Abstract: We divide "intelligence" into multiple dimensions (like ...

Uncertainty for Active Learning on Graphs (ICML 2024)

Uncertainty for Active Learning on Graphs (ICML 2024)

Uncertainty Sampling is an Active

ICML2024

ICML2024

Generalization Error of

[ICML 2024] Individual Fairness in Graph Decomposition

[ICML 2024] Individual Fairness in Graph Decomposition

[ICML 2024] Individual Fairness in Graph Decomposition