Cover Image

mHC-GNN: Manifold-Constrained Hyper-Connections for Graph Neural Networks

Fuente: arXiv

Saved in:

Bibliographic Details
Main Author:	Mishra, Subhankar
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

mHC: Manifold-Constrained Hyper-Connections
by: Xie, Zhenda, et al.
Published: (2025)

mHC-SSM: Manifold-Constrained Hyper-Connections for State Space Language Models with Stream-Specialized Adapters
by: Mutlu, Abdulvahap, et al.
Published: (2026)

mHC-lite: You Don't Need 20 Sinkhorn-Knopp Iterations
by: Yang, Yongyi, et al.
Published: (2026)

JPmHC Dynamical Isometry via Orthogonal Hyper-Connections
by: Sengupta, Biswa, et al.
Published: (2026)

Towards Metric-Faithful Neural Graph Matching
by: Shivottam, Jyotirmaya, et al.
Published: (2026)

Graph Neural Networks at a Fraction
by: Joshi, Rucha Bhalchandra, et al.
Published: (2025)

QGShap: Quantum Acceleration for Faithful GNN Explanations
by: Jena, Haribandhu, et al.
Published: (2025)

HT-GNN: Hyper-Temporal Graph Neural Network for Customer Lifetime Value Prediction in Baidu Ads
by: Zhao, Xiaohui, et al.
Published: (2026)

LiGNN: Graph Neural Networks at LinkedIn
by: Borisyuk, Fedor, et al.
Published: (2024)

KromHC: Manifold-Constrained Hyper-Connections with Kronecker-Product Residual Matrices
by: Zhou, Wuyang, et al.
Published: (2026)

go-$m$HC: Direct Parameterization of Manifold-Constrained Hyper-Connections via Generalized Orthostochastic Matrices
by: Dandachi, Torque, et al.
Published: (2026)

Beyond the Birkhoff Polytope: Spectral-Sphere-Constrained Hyper-Connections
by: Liu, Zhaoyi, et al.
Published: (2026)

ComFairGNN: Community Fair Graph Neural Network
by: Sium, Yonas, et al.
Published: (2024)

LPS-GNN : Deploying Graph Neural Networks on Graphs with 100-Billion Edges
by: Cheng, Xu, et al.
Published: (2025)

Sketch-GNN: Scalable Graph Neural Networks with Sublinear Training Complexity
by: Ding, Mucong, et al.
Published: (2024)

Framework GNN-AID: Graph Neural Network Analysis Interpretation and Defense
by: Lukyanov, Kirill, et al.
Published: (2025)

Enhancing Neural Theorem Proving through Data Augmentation and Dynamic Sampling Method
by: Vishwakarma, Rahul, et al.
Published: (2023)

QGraphLIME - Explaining Quantum Graph Neural Networks
by: Jena, Haribandhu, et al.
Published: (2025)

LightGNN: Simple Graph Neural Network for Recommendation
by: Chen, Guoxuan, et al.
Published: (2025)

SAGMAN: Stability Analysis of Graph Neural Networks on the Manifolds
by: Cheng, Wuxinlin, et al.
Published: (2024)

DUALFloodGNN: Physics-informed Graph Neural Network for Operational Flood Modeling
by: Acosta, Carlo Malapad, et al.
Published: (2025)

FSW-GNN: A Bi-Lipschitz WL-Equivalent Graph Neural Network
by: Sverdlov, Yonatan, et al.
Published: (2024)

DFA-GNN: Forward Learning of Graph Neural Networks by Direct Feedback Alignment
by: Zhao, Gongpei, et al.
Published: (2024)

GNN-VPA: A Variance-Preserving Aggregation Strategy for Graph Neural Networks
by: Schneckenreiter, Lisa, et al.
Published: (2024)

SCL-GNN: Towards Generalizable Graph Neural Networks via Spurious Correlation Learning
by: Zhang, Yuxiang, et al.
Published: (2026)

GNN-XAR: A Graph Neural Network for Explainable Activity Recognition in Smart Homes
by: Fiori, Michele, et al.
Published: (2025)

E2GNN: Efficient Graph Neural Network Ensembles for Semi-Supervised Classification
by: Zhang, Xin, et al.
Published: (2024)

SF-GNN: Self Filter for Message Lossless Propagation in Deep Graph Neural Network
by: Zhu, Yushan, et al.
Published: (2024)

RoCP-GNN: Robust Conformal Prediction for Graph Neural Networks in Node-Classification
by: Akansha, S.
Published: (2024)

Unveiling Mode Connectivity in Graph Neural Networks
by: Li, Bingheng, et al.
Published: (2025)

FreeGNN: Continual Source-Free Graph Neural Network Adaptation for Renewable Energy Forecasting
by: Bahi, Abderaouf, et al.
Published: (2026)

RapidGNN: Energy and Communication-Efficient Distributed Training on Large-Scale Graph Neural Networks
by: Niam, Arefin, et al.
Published: (2025)

SpanGNN: Towards Memory-Efficient Graph Neural Networks via Spanning Subgraph Training
by: Gu, Xizhi, et al.
Published: (2024)

HC-GAE: The Hierarchical Cluster-based Graph Auto-Encoder for Graph Representation Learning
by: Xu, Zhuo, et al.
Published: (2024)

Can we ease the Injectivity Bottleneck on Lorentzian Manifolds for Graph Neural Networks?
by: Srinivasan, Srinitish, et al.
Published: (2025)

RAG-GNN: Integrating Retrieved Knowledge with Graph Neural Networks for Precision Medicine
by: Hays, Hasi, et al.
Published: (2026)

Deep Manifold Part 1: Anatomy of Neural Network Manifold
by: Ma, Max Y., et al.
Published: (2024)

WaveGNN: Integrating Graph Neural Networks and Transformers for Decay-Aware Classification of Irregular Clinical Time-Series
by: Hajisafi, Arash, et al.
Published: (2024)

AdS-GNN -- a Conformally Equivariant Graph Neural Network
by: Zhdanov, Maksim, et al.
Published: (2025)

Frac-Connections: Fractional Extension of Hyper-Connections
by: Zhu, Defa, et al.
Published: (2025)