Image de couverture de livre

CORGI: GNNs with Convolutional Residual Global Interactions for Lagrangian Simulation

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Ji, Ethan, Chen, Yuanzhou, Ramteke, Arush, Sun, Fang, Yu, Tianrun, Parera, Jai, Wang, Wei, Sun, Yizhou
Format:	Preprint
Publié:	2025
Sujets:	Machine Learning
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Physics-Informed Regularization for Domain-Agnostic Dynamical System Modeling
par: Huang, Zijie, et autres
Publié: (2024)

Adaptive Initial Residual Connections for GNNs with Theoretical Guarantees
par: Shirzadi, Mohammad, et autres
Publié: (2025)

Residual Connections and Normalization Can Provably Prevent Oversmoothing in GNNs
par: Scholkemper, Michael, et autres
Publié: (2024)

Do Contemporary Causal Inference Models Capture Real-World Heterogeneity? Findings from a Large-Scale Benchmark
par: Yu, Haining, et autres
Publié: (2024)

Revealing Combinatorial Reasoning of GNNs via Graph Concept Bottleneck Layer
par: Niu, Yue, et autres
Publié: (2026)

Hierarchical Attention Models for Multi-Relational Graphs
par: Iyer, Roshni G., et autres
Publié: (2024)

Nonparametric Classification on Low Dimensional Manifolds using Overparameterized Convolutional Residual Networks
par: Zhang, Zixuan, et autres
Publié: (2023)

FD-Bench: A Modular and Fair Benchmark for Data-driven Fluid Simulation
par: Wang, Haixin, et autres
Publié: (2025)

Empowering GNNs via Edge-Aware Weisfeiler-Leman Algorithm
par: Liu, Meng, et autres
Publié: (2022)

LLM Assertiveness can be Mechanistically Decomposed into Emotional and Logical Components
par: Tsujimura, Hikaru, et autres
Publié: (2025)

Residual Hyperbolic Graph Convolution Networks
par: Xue, Yangkai, et autres
Publié: (2024)

Enhance the Safety in Reinforcement Learning by ADRC Lagrangian Methods
par: Zhang, Mingxu, et autres
Publié: (2026)

Feature Augmentation of GNNs for ILPs: Local Uniqueness Suffices
par: Han, Qingyu, et autres
Publié: (2025)

Simulator and Experience Enhanced Diffusion Model for Comprehensive ECG Generation
par: Wang, Xiaoda, et autres
Publié: (2025)

Recent Developments in GNNs for Drug Discovery
par: Fang, Zhengyu, et autres
Publié: (2025)

Position: Spectral GNNs Are Neither Spectral Nor Superior for Node Classification
par: Jiang, Qin, et autres
Publié: (2026)

Differentiable Sparse Identification of Lagrangian Dynamics
par: Zhang, Zitong, et autres
Publié: (2025)

Bayesian Intervention Optimization for Causal Discovery
par: Wang, Yuxuan, et autres
Publié: (2024)

WorldParticle: Unified World Simulation of Lagrangian Particle Dynamics via Transformer
par: Wang, Caoliwen, et autres
Publié: (2026)

Universally Invariant Learning in Equivariant GNNs
par: Cen, Jiacheng, et autres
Publié: (2025)

Causal Discovery via Conditional Independence Testing with Proxy Variables
par: Liu, Mingzhou, et autres
Publié: (2023)

Accelerating Time Series Foundation Models with Speculative Decoding
par: Subbaraman, Pranav, et autres
Publié: (2025)

From GNNs to Trees: Multi-Granular Interpretability for Graph Neural Networks
par: Yang, Jie, et autres
Publié: (2025)

Classic GNNs are Strong Baselines: Reassessing GNNs for Node Classification
par: Luo, Yuankai, et autres
Publié: (2024)

Conditional Local Independence Testing for Itô processes with Applications to Dynamic Causal Discovery
par: Liu, Mingzhou, et autres
Publié: (2025)

Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy
par: Xue, Ruizhan, et autres
Publié: (2025)

On the Effect of Sampling Diversity in Scaling LLM Inference
par: Wang, Tianchun, et autres
Publié: (2025)

EqCollide: Equivariant and Collision-Aware Deformable Objects Neural Simulator
par: Chen, Qianyi, et autres
Publié: (2025)

Graph Fourier Neural ODEs: Modeling Spatial-temporal Multi-scales in Molecular Dynamics
par: Sun, Fang, et autres
Publié: (2024)

Fine-tuning is Not Fine: Mitigating Backdoor Attacks in GNNs with Limited Clean Data
par: Zhang, Jiale, et autres
Publié: (2025)

MoE-Beyond: Learning-Based Expert Activation Prediction on Edge Devices
par: Gavhane, Nishant, et autres
Publié: (2025)

Learned Lagrangian Models of PDEs via Euler-Lagrange Residual Minimization
par: Zhornyak, Lyra, et autres
Publié: (2026)

Graph-augmented Convolutional Networks on Drug-Drug Interactions Prediction
par: Zhong, Yi, et autres
Publié: (2019)

The Heterophilic Snowflake Hypothesis: Training and Empowering GNNs for Heterophilic Graphs
par: Wang, Kun, et autres
Publié: (2024)

Mixture of In-Context Prompters for Tabular PFNs
par: Xu, Derek, et autres
Publié: (2024)

MuGSI: Distilling GNNs with Multi-Granularity Structural Information for Graph Classification
par: Yao, Tianjun, et autres
Publié: (2024)

Spectral Heterogeneous Graph Convolutions via Positive Noncommutative Polynomials
par: He, Mingguo, et autres
Publié: (2023)

How Hard Is It for Message-Passing GNNs to Simulate One Weisfeiler-Lehman Color-Refinement Step?
par: Cui, Guanyu, et autres
Publié: (2024)

Unlink to Unlearn: Simplifying Edge Unlearning in GNNs
par: Tan, Jiajun, et autres
Publié: (2024)

Scalable Graph Compressed Convolutions
par: Sun, Junshu, et autres
Publié: (2024)