Robust Angular Synchronization via Directed Graph Neural Networks
Fuente:
arXiv
Saved in:
| Main Authors: | He, Yixuan, Reinert, Gesine, Wipf, David, Cucuringu, Mihai |
|---|---|
| Format: | Preprint |
| Published: |
2023
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Learning to Fuse Temporal Proximity Networks: A Case Study in Chimpanzee Social Interactions
by: He, Yixuan, et al.
Published: (2025)
by: He, Yixuan, et al.
Published: (2025)
Solving Max-Cut to Global Optimality via Feasibility-Preserving Graph Neural Networks
by: Chen, Hao, et al.
Published: (2026)
by: Chen, Hao, et al.
Published: (2026)
Wasserstein Distributionally Robust Shallow Convex Neural Networks
by: Pallage, Julien, et al.
Published: (2024)
by: Pallage, Julien, et al.
Published: (2024)
Early Directional Convergence in Deep Homogeneous Neural Networks for Small Initializations
by: Kumar, Akshay, et al.
Published: (2024)
by: Kumar, Akshay, et al.
Published: (2024)
Rethinking the Capacity of Graph Neural Networks for Branching Strategy
by: Chen, Ziang, et al.
Published: (2024)
by: Chen, Ziang, et al.
Published: (2024)
Directional Convergence Near Small Initializations and Saddles in Two-Homogeneous Neural Networks
by: Kumar, Akshay, et al.
Published: (2024)
by: Kumar, Akshay, et al.
Published: (2024)
Distributed Control of Network Systems in the Space of Stabilizing Graph Neural Network Policies
by: Cao, John, et al.
Published: (2025)
by: Cao, John, et al.
Published: (2025)
Tight Robustness Certificates and Wasserstein Distributional Attacks for Deep Neural Networks
by: Le, Bach C., et al.
Published: (2025)
by: Le, Bach C., et al.
Published: (2025)
Expressive Power of Graph Neural Networks for (Mixed-Integer) Quadratic Programs
by: Chen, Ziang, et al.
Published: (2024)
by: Chen, Ziang, et al.
Published: (2024)
Convergence of Spectral Descent for Non-smooth Optimization
by: Yang, Yixuan, et al.
Published: (2026)
by: Yang, Yixuan, et al.
Published: (2026)
Towards Optimal Branching of Linear and Semidefinite Relaxations for Neural Network Robustness Certification
by: Anderson, Brendon G., et al.
Published: (2021)
by: Anderson, Brendon G., et al.
Published: (2021)
Physics-Informed Graph Neural Network for Dynamic Reconfiguration of Power Systems
by: Authier, Jules, et al.
Published: (2023)
by: Authier, Jules, et al.
Published: (2023)
Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks
by: Noel, Molly, et al.
Published: (2025)
by: Noel, Molly, et al.
Published: (2025)
The Ground Cost for Optimal Transport of Angular Velocity
by: Elamvazhuthi, Karthik, et al.
Published: (2025)
by: Elamvazhuthi, Karthik, et al.
Published: (2025)
Multi-Objective Linear Ensembles for Robust and Sparse Training of Few-Bit Neural Networks
by: Bernardelli, Ambrogio Maria, et al.
Published: (2022)
by: Bernardelli, Ambrogio Maria, et al.
Published: (2022)
L2G2G: a Scalable Local-to-Global Network Embedding with Graph Autoencoders
by: Ouyang, Ruikang, et al.
Published: (2024)
by: Ouyang, Ruikang, et al.
Published: (2024)
Solving Integrated Process Planning and Scheduling Problem via Graph Neural Network Based Deep Reinforcement Learning
by: Li, Hongpei, et al.
Published: (2024)
by: Li, Hongpei, et al.
Published: (2024)
Learn2Aggregate: Supervised Generation of Chvátal-Gomory Cuts Using Graph Neural Networks
by: Deza, Arnaud, et al.
Published: (2024)
by: Deza, Arnaud, et al.
Published: (2024)
Distributionally Robust Safety Verification of Neural Networks via Worst-Case CVaR
by: Kishida, Masako
Published: (2025)
by: Kishida, Masako
Published: (2025)
Boosting Column Generation with Graph Neural Networks for Joint Rider Trip Planning and Crew Shift Scheduling
by: Lu, Jiawei, et al.
Published: (2024)
by: Lu, Jiawei, et al.
Published: (2024)
Robust Gaussian Processes via Relevance Pursuit
by: Ament, Sebastian, et al.
Published: (2024)
by: Ament, Sebastian, et al.
Published: (2024)
Adversary-Robust Learning from Fully Asynchronous Directional Derivative Estimates
by: Paul, Anik Kumar, et al.
Published: (2026)
by: Paul, Anik Kumar, et al.
Published: (2026)
Assessing and Enhancing Graph Neural Networks for Combinatorial Optimization: Novel Approaches and Application in Maximum Independent Set Problems
by: Hu, Chenchuhui
Published: (2024)
by: Hu, Chenchuhui
Published: (2024)
Active Learning of Deep Neural Networks via Gradient-Free Cutting Planes
by: Zhang, Erica, et al.
Published: (2024)
by: Zhang, Erica, et al.
Published: (2024)
Sample-Free Safety Assessment of Neural Network Controllers via Taylor Methods
by: Evans, Adam, et al.
Published: (2026)
by: Evans, Adam, et al.
Published: (2026)
Constant Stepsize Q-learning: Distributional Convergence, Bias and Extrapolation
by: Zhang, Yixuan, et al.
Published: (2024)
by: Zhang, Yixuan, et al.
Published: (2024)
Scalable Solution of the Stochastic Multi-path Traveling Salesman Problem via Neural Networks
by: Chou, Xiaochen, et al.
Published: (2026)
by: Chou, Xiaochen, et al.
Published: (2026)
Provably Convergent Decentralized Optimization over Directed Graphs under Generalized Smoothness
by: Bo, Yanan, et al.
Published: (2026)
by: Bo, Yanan, et al.
Published: (2026)
Stability and Generalization of Push-Sum Based Decentralized Optimization over Directed Graphs
by: Liang, Yifei, et al.
Published: (2026)
by: Liang, Yifei, et al.
Published: (2026)
Optimal Depth of Neural Networks
by: Qi, Qian
Published: (2025)
by: Qi, Qian
Published: (2025)
KKT-Informed Neural Network
by: Femine, Carmine Delle
Published: (2024)
by: Femine, Carmine Delle
Published: (2024)
Reinforcement Learning-based Control via Y-wise Affine Neural Networks (YANNs)
by: Braniff, Austin, et al.
Published: (2025)
by: Braniff, Austin, et al.
Published: (2025)
Universal Approximation Power of Deep Residual Neural Networks via Nonlinear Control Theory
by: Tabuada, Paulo, et al.
Published: (2020)
by: Tabuada, Paulo, et al.
Published: (2020)
Information Theoretically Optimal Sample Complexity of Learning Dynamical Directed Acyclic Graphs
by: Veedu, Mishfad Shaikh, et al.
Published: (2023)
by: Veedu, Mishfad Shaikh, et al.
Published: (2023)
Learning Aligned Stability in Neural ODEs Reconciling Accuracy with Robustness
by: Luo, Chaoyang, et al.
Published: (2025)
by: Luo, Chaoyang, et al.
Published: (2025)
A Nonlinear Separation Principle via Contraction Theory: Applications to Neural Networks, Control, and Learning
by: Gokhale, Anand, et al.
Published: (2026)
by: Gokhale, Anand, et al.
Published: (2026)
Curse of Dimensionality in Neural Network Optimization
by: Na, Sanghoon, et al.
Published: (2025)
by: Na, Sanghoon, et al.
Published: (2025)
On the Topology of Neural Network Superlevel Sets
by: Gharesifard, Bahman
Published: (2026)
by: Gharesifard, Bahman
Published: (2026)
Learning Neural Networks by Neuron Pursuit
by: Kumar, Akshay, et al.
Published: (2025)
by: Kumar, Akshay, et al.
Published: (2025)
Certified Robust Invariant Polytope Training in Neural Controlled ODEs
by: Harapanahalli, Akash, et al.
Published: (2024)
by: Harapanahalli, Akash, et al.
Published: (2024)
Similar Items
-
Learning to Fuse Temporal Proximity Networks: A Case Study in Chimpanzee Social Interactions
by: He, Yixuan, et al.
Published: (2025) -
Solving Max-Cut to Global Optimality via Feasibility-Preserving Graph Neural Networks
by: Chen, Hao, et al.
Published: (2026) -
Wasserstein Distributionally Robust Shallow Convex Neural Networks
by: Pallage, Julien, et al.
Published: (2024) -
Early Directional Convergence in Deep Homogeneous Neural Networks for Small Initializations
by: Kumar, Akshay, et al.
Published: (2024) -
Rethinking the Capacity of Graph Neural Networks for Branching Strategy
by: Chen, Ziang, et al.
Published: (2024)