Graph Neural Networks for Edge Signals: Orientation Equivariance and Invariance
Fuente:
arXiv
Saved in:
| Main Authors: | Fuchsgruber, Dominik, Poštuvan, Tim, Günnemann, Stephan, Geisler, Simon |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Energy-based Epistemic Uncertainty for Graph Neural Networks
by: Fuchsgruber, Dominik, et al.
Published: (2024)
by: Fuchsgruber, Dominik, et al.
Published: (2024)
Task-Awareness Improves LLM Generations and Uncertainty
by: Tomov, Tim, et al.
Published: (2026)
by: Tomov, Tim, et al.
Published: (2026)
Task-Aware Calibration: Provably Optimal Decoding in LLMs
by: Tomov, Tim, et al.
Published: (2026)
by: Tomov, Tim, et al.
Published: (2026)
The Illusion of Certainty: Uncertainty Quantification for LLMs Fails under Ambiguity
by: Tomov, Tim, et al.
Published: (2025)
by: Tomov, Tim, et al.
Published: (2025)
Spatio-Spectral Graph Neural Networks
by: Geisler, Simon, et al.
Published: (2024)
by: Geisler, Simon, et al.
Published: (2024)
Uncertainty Estimation for Heterophilic Graphs Through the Lens of Information Theory
by: Fuchsgruber, Dominik, et al.
Published: (2025)
by: Fuchsgruber, Dominik, et al.
Published: (2025)
Uncertainty for Active Learning on Graphs
by: Fuchsgruber, Dominik, et al.
Published: (2024)
by: Fuchsgruber, Dominik, et al.
Published: (2024)
Randomized Message-Interception Smoothing: Gray-box Certificates for Graph Neural Networks
by: Scholten, Yan, et al.
Published: (2023)
by: Scholten, Yan, et al.
Published: (2023)
Long-Range Graph Wavelet Networks
by: Guerranti, Filippo, et al.
Published: (2025)
by: Guerranti, Filippo, et al.
Published: (2025)
Explainable Graph Neural Networks Under Fire
by: Li, Zhong, et al.
Published: (2024)
by: Li, Zhong, et al.
Published: (2024)
On Representing Electronic Wave Functions with Sign Equivariant Neural Networks
by: Gao, Nicholas, et al.
Published: (2024)
by: Gao, Nicholas, et al.
Published: (2024)
Adversarial Robustness of Graph Transformers
by: Foth, Philipp, et al.
Published: (2024)
by: Foth, Philipp, et al.
Published: (2024)
Adversarial Attacks on Graph Neural Networks via Meta Learning
by: Zügner, Daniel, et al.
Published: (2019)
by: Zügner, Daniel, et al.
Published: (2019)
SAFT: Structure-Aware Fine-Tuning of LLMs for AMR-to-Text Generation
by: Kamel, Rafiq, et al.
Published: (2025)
by: Kamel, Rafiq, et al.
Published: (2025)
Provable Adversarial Robustness for Group Equivariant Tasks: Graphs, Point Clouds, Molecules, and More
by: Schuchardt, Jan, et al.
Published: (2023)
by: Schuchardt, Jan, et al.
Published: (2023)
GemNet: Universal Directional Graph Neural Networks for Molecules
by: Gasteiger, Johannes, et al.
Published: (2021)
by: Gasteiger, Johannes, et al.
Published: (2021)
Learning-Based Link Anomaly Detection in Continuous-Time Dynamic Graphs
by: Poštuvan, Tim, et al.
Published: (2024)
by: Poštuvan, Tim, et al.
Published: (2024)
Exact Certification of (Graph) Neural Networks Against Label Poisoning
by: Sabanayagam, Mahalakshmi, et al.
Published: (2024)
by: Sabanayagam, Mahalakshmi, et al.
Published: (2024)
Attacking Large Language Models with Projected Gradient Descent
by: Geisler, Simon, et al.
Published: (2024)
by: Geisler, Simon, et al.
Published: (2024)
Provable Robustness of (Graph) Neural Networks Against Data Poisoning and Backdoor Attacks
by: Gosch, Lukas, et al.
Published: (2024)
by: Gosch, Lukas, et al.
Published: (2024)
Learning Equivariant Non-Local Electron Density Functionals
by: Gao, Nicholas, et al.
Published: (2024)
by: Gao, Nicholas, et al.
Published: (2024)
Expressivity of Graph Neural Networks Through the Lens of Adversarial Robustness
by: Campi, Francesco, et al.
Published: (2023)
by: Campi, Francesco, et al.
Published: (2023)
Geometry of Linear Neural Networks: Equivariance and Invariance under Permutation Groups
by: Kohn, Kathlén, et al.
Published: (2023)
by: Kohn, Kathlén, et al.
Published: (2023)
REINFORCE Adversarial Attacks on Large Language Models: An Adaptive, Distributional, and Semantic Objective
by: Geisler, Simon, et al.
Published: (2025)
by: Geisler, Simon, et al.
Published: (2025)
Relaxed Equivariant Graph Neural Networks
by: Hofgard, Elyssa, et al.
Published: (2024)
by: Hofgard, Elyssa, et al.
Published: (2024)
The Geometry of Refusal in Large Language Models: Concept Cones and Representational Independence
by: Wollschläger, Tom, et al.
Published: (2025)
by: Wollschläger, Tom, et al.
Published: (2025)
Model Metamers Reveal Invariances in Graph Neural Networks
by: Xu, Wei, et al.
Published: (2025)
by: Xu, Wei, et al.
Published: (2025)
Towards Invariance to Node Identifiers in Graph Neural Networks
by: Bechler-Speicher, Maya, et al.
Published: (2025)
by: Bechler-Speicher, Maya, et al.
Published: (2025)
Neural Pfaffians: Solving Many Many-Electron Schrödinger Equations
by: Gao, Nicholas, et al.
Published: (2024)
by: Gao, Nicholas, et al.
Published: (2024)
Exact Certification of Neural Networks and Partition Aggregation Ensembles against Label Poisoning
by: Mohgaonkar, Ajinkya, et al.
Published: (2026)
by: Mohgaonkar, Ajinkya, et al.
Published: (2026)
Sampling-aware Adversarial Attacks Against Large Language Models
by: Beyer, Tim, et al.
Published: (2025)
by: Beyer, Tim, et al.
Published: (2025)
Provably Reliable Conformal Prediction Sets in the Presence of Data Poisoning
by: Scholten, Yan, et al.
Published: (2024)
by: Scholten, Yan, et al.
Published: (2024)
Shaving Weights with Occam's Razor: Bayesian Sparsification for Neural Networks Using the Marginal Likelihood
by: Dhahri, Rayen, et al.
Published: (2024)
by: Dhahri, Rayen, et al.
Published: (2024)
Discrete Bayesian Sample Inference for Graph Generation
by: Petersen, Ole, et al.
Published: (2025)
by: Petersen, Ole, et al.
Published: (2025)
Constructing 3D Rotational Invariance and Equivariance with Symmetric Tensor Networks
by: Zhang, Meng, et al.
Published: (2025)
by: Zhang, Meng, et al.
Published: (2025)
Graph Neural Networks for Learning Equivariant Representations of Neural Networks
by: Kofinas, Miltiadis, et al.
Published: (2024)
by: Kofinas, Miltiadis, et al.
Published: (2024)
SEIS: Subspace-based Equivariance and Invariance Scores for Neural Representations
by: Lin, Huahua, et al.
Published: (2026)
by: Lin, Huahua, et al.
Published: (2026)
Joint Relational Database Generation via Graph-Conditional Diffusion Models
by: Ketata, Mohamed Amine, et al.
Published: (2025)
by: Ketata, Mohamed Amine, et al.
Published: (2025)
Graph Automorphism Group Equivariant Neural Networks
by: Pearce-Crump, Edward, et al.
Published: (2023)
by: Pearce-Crump, Edward, et al.
Published: (2023)
Accurate and Scalable Graph Neural Networks via Message Invariance
by: Shi, Zhihao, et al.
Published: (2025)
by: Shi, Zhihao, et al.
Published: (2025)
Similar Items
-
Energy-based Epistemic Uncertainty for Graph Neural Networks
by: Fuchsgruber, Dominik, et al.
Published: (2024) -
Task-Awareness Improves LLM Generations and Uncertainty
by: Tomov, Tim, et al.
Published: (2026) -
Task-Aware Calibration: Provably Optimal Decoding in LLMs
by: Tomov, Tim, et al.
Published: (2026) -
The Illusion of Certainty: Uncertainty Quantification for LLMs Fails under Ambiguity
by: Tomov, Tim, et al.
Published: (2025) -
Spatio-Spectral Graph Neural Networks
by: Geisler, Simon, et al.
Published: (2024)