Cover Image

GraphComp: Extreme Error-bounded Compression of Scientific Data via Temporal Graph Autoencoders

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Li, Guozhong, Alhumaidi, Muhannad, Skiadopoulos, Spiros, Hoteit, Ibrahim, Kalnis, Panos
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

LLMComp: A Language Modeling Paradigm for Error-Bounded Scientific Data Compression (Technical Report)
by: Li, Guozhong, et al.
Published: (2025)

Task-Oriented GNNs Training on Large Knowledge Graphs for Accurate and Efficient Modeling
by: Abdallah, Hussein, et al.
Published: (2024)

ART: Attention Run-time Termination for Efficient Large Language Model Decoding
by: Qiu, Chen, et al.
Published: (2026)

StructComp: Substituting Propagation with Structural Compression in Training Graph Contrastive Learning
by: Zhang, Shengzhong, et al.
Published: (2023)

Sparse $L^1$-Autoencoders for Scientific Data Compression
by: Chung, Matthias, et al.
Published: (2024)

RED: Effective Trajectory Representation Learning with Comprehensive Information
by: Zhou, Silin, et al.
Published: (2024)

Spatially Regularized Graph Attention Autoencoder Framework for Detecting Rainfall Extremes
by: Agarwal, Mihir, et al.
Published: (2024)

CHESS: Context-aware Hierarchical Efficient Semantic Selection for Long-Context LLM Inference
by: Fei, Chao, et al.
Published: (2026)

HGAurban: Heterogeneous Graph Autoencoding for Urban Spatial-Temporal Learning
by: Zhang, Qianru, et al.
Published: (2024)

LLMs Meet Cross-Modal Time Series Analytics: Overview and Directions
by: Liu, Chenxi, et al.
Published: (2025)

Leveraging LLM-GNN Integration for Open-World Question Answering over Knowledge Graphs
by: Abdallah, Hussein, et al.
Published: (2026)

Masked BRep Autoencoder via Hierarchical Graph Transformer
by: Li, Yifei, et al.
Published: (2026)

A Variational Autoencoder for Neural Temporal Point Processes with Dynamic Latent Graphs
by: Yang, Sikun, et al.
Published: (2023)

Principled Latent Diffusion for Graphs via Laplacian Autoencoders
by: Siraudin, Antoine, et al.
Published: (2026)

Exploring Variational Graph Autoencoders for Distribution Grid Data Generation
by: Abbas, Syed Zain, et al.
Published: (2025)

Graph Positional Autoencoders as Self-supervised Learners
by: Liu, Yang, et al.
Published: (2025)

IVGAE: Handling Incomplete Heterogeneous Data with a Variational Graph Autoencoder
by: Zhou, Youran, et al.
Published: (2025)

Hierarchical Autoencoder-based Lossy Compression for Large-scale High-resolution Scientific Data
by: Le, Hieu, et al.
Published: (2023)

JaGuard: Position Error Correction of GNSS Jamming with Deep Temporal Graphs
by: Kesić, Ivana, et al.
Published: (2025)

FOS: A Large-Scale Temporal Graph Benchmark for Scientific Interdisciplinary Link Prediction
by: Rezaee, Kiyan, et al.
Published: (2025)

Foundation Model for Lossy Compression of Spatiotemporal Scientific Data
by: Li, Xiao, et al.
Published: (2024)

Unsupervised Feature Selection via Robust Autoencoder and Adaptive Graph Learning
by: Yu, Feng, et al.
Published: (2025)

Graph Autoencoder for Process Monitoring
by: Zhang, Xiangrui
Published: (2026)

Forecasting Multivariate Urban Data via Decomposition and Spatio-Temporal Graph Analysis
by: Sohrabbeig, Amirhossein, et al.
Published: (2025)

Graph Generative Models Evaluation with Masked Autoencoder
by: Wang, Chengen, et al.
Published: (2025)

Hi-GMAE: Hierarchical Graph Masked Autoencoders
by: Liu, Chuang, et al.
Published: (2024)

Conformal Load Prediction with Transductive Graph Autoencoders
by: Luo, Rui, et al.
Published: (2024)

OLGA: One-cLass Graph Autoencoder
by: Gôlo, M. P. S., et al.
Published: (2024)

Stabilizing Temporal Difference Learning via Implicit Stochastic Recursion
by: Kim, Hwanwoo, et al.
Published: (2025)

Masked Graph Autoencoder with Non-discrete Bandwidths
by: Zhao, Ziwen, et al.
Published: (2024)

GraphCroc: Cross-Correlation Autoencoder for Graph Structural Reconstruction
by: Duan, Shijin, et al.
Published: (2024)

Preserving Node Distinctness in Graph Autoencoders via Similarity Distillation
by: Chen, Ge, et al.
Published: (2024)

Revisiting Graph Autoencoders as Implicit Contrastive Learners
by: Li, Jintang, et al.
Published: (2024)

Inference-friendly Graph Compression for Graph Neural Networks
by: Fan, Yangxin, et al.
Published: (2025)

An Edge-Aware Graph Autoencoder Trained on Scale-Imbalanced Data for Traveling Salesman Problems
by: Liu, Shiqing, et al.
Published: (2023)

Generalized Graph Transformer Variational Autoencoder
by: Karki, Siddhant
Published: (2025)

Scalable Graph Compressed Convolutions
by: Sun, Junshu, et al.
Published: (2024)

Fully-Connected Spatial-Temporal Graph for Multivariate Time-Series Data
by: Wang, Yucheng, et al.
Published: (2023)

Modeling Spatio-temporal Extremes via Conditional Variational Autoencoders
by: Ma, Xiaoyu, et al.
Published: (2025)

ReCycle: Resilient Training of Large DNNs using Pipeline Adaptation
by: Gandhi, Swapnil, et al.
Published: (2024)