ArchEGraph: A Large-Scale Graph Dataset for Geometry-Topology-Physics Aligned Building Energy Modeling

arXiv:2608.06772 · cs.LG · Submitted 2026-08-07 · Read on arXiv

Yihui Li, Yihui Chen, Kaidi Zha, Xiaoyue Yan, Zhexuan Yu, Shiqi Dai, Jun Xiao, Jun Yin, Ramon Elias Weber, Borong Lin

cs.LG

Submitted: 2026-08-07

Updated: 2026-08-10

Comments: 26 pages, 13 figures, submitted to a conference

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

Benchmark — 26× in this paper · explained in 2 episodes
Generalization — 22× in this paper · explained in 14 episodes
Heterogeneous Graph — 10× in this paper · explained in 2 episodes
Robustness — 10× in this paper · explained in 6 episodes
Surrogate Model — 8× in this paper · explained in 3 episodes
Surrogate Models — 8× in this paper · explained in 3 episodes
Consistency — 7× in this paper · explained in 3 episodes
Accuracy — 5× in this paper · explained in 1 episode
Distribution Shift — 5× in this paper · explained in 12 episodes
Transformer — 5× in this paper · explained in 2 episodes
Evaluation Protocol — 4× in this paper · explained in 2 episodes
Abstraction — 3× in this paper · explained in 1 episode
Embeddings — 3× in this paper · explained in 2 episodes
Transfer Learning — 3× in this paper · explained in 16 episodes
Adam — 2× in this paper · explained in 3 episodes
Composition — 2× in this paper · explained in 2 episodes
Data Leakage — 2× in this paper · explained in 2 episodes
Decoder — 2× in this paper · explained in 2 episodes
Elias — 2× in this paper · explained in 2 episodes
Inductive Bias — 2× in this paper · explained in 3 episodes
International Conference on Machine Learning — 2× in this paper
National Renewable Energy Laboratory — 2× in this paper
Ontology — 2× in this paper · explained in 2 episodes
Point Clouds — 2× in this paper · explained in 2 episodes
Representation Learning — 2× in this paper · explained in 3 episodes
Training Objective — 2× in this paper · explained in 3 episodes
Transformer Encoder — 2× in this paper · explained in 2 episodes
Ablation — 1× in this paper · explained in 1 episode
Augmentation — 1× in this paper · explained in 2 episodes
Benchmarking — 1× in this paper · explained in 4 episodes
Class Imbalance — 1× in this paper · explained in 3 episodes
Clustering — 1× in this paper · explained in 2 episodes
Computational Efficiency — 1× in this paper · explained in 2 episodes
Core — 1× in this paper · explained in 2 episodes
Distribution Shifts — 1× in this paper · explained in 2 episodes
Energy Efficiency — 1× in this paper · explained in 4 episodes
Expressivity — 1× in this paper · explained in 2 episodes
F1 Score — 1× in this paper · explained in 4 episodes
False Negatives — 1× in this paper · explained in 2 episodes
Fidelity — 1× in this paper · explained in 2 episodes
Generative Model — 1× in this paper · explained in 2 episodes
Generative Models — 1× in this paper · explained in 3 episodes
Heavy-Tailed Distributions — 1× in this paper · explained in 2 episodes
Hybrid Approaches — 1× in this paper · explained in 2 episodes
Hypergraph — 1× in this paper · explained in 2 episodes
Nadia — 1× in this paper · explained in 2 episodes
Parameterization — 1× in this paper · explained in 2 episodes
Physicsbased Building Performance Simulation — 1× in this paper
Redundancy — 1× in this paper · explained in 2 episodes
Topological Defects — 1× in this paper · explained in 3 episodes
Weight Decay — 1× in this paper · explained in 2 episodes

Terminology

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