Saved in:
| Main Authors: | Yang, Minglai, Ahmed, Reyan |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2509.17333 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
CoRe-GD: A Hierarchical Framework for Scalable Graph Visualization with GNNs
by: Grötschla, Florian, et al.
Published: (2024)
by: Grötschla, Florian, et al.
Published: (2024)
Size Should not Matter: Scale-invariant Stress Metrics
by: Ahmed, Reyan, et al.
Published: (2024)
by: Ahmed, Reyan, et al.
Published: (2024)
Graph Drawing Stress Model with Resistance Distances
by: Onoue, Yosuke
Published: (2025)
by: Onoue, Yosuke
Published: (2025)
Ironing the Graphs: Toward a Correct Geometric Analysis of Large-Scale Graphs
by: Naama, Saloua, et al.
Published: (2024)
by: Naama, Saloua, et al.
Published: (2024)
Topological Spatial Graph Coarsening
by: Calissano, Anna, et al.
Published: (2025)
by: Calissano, Anna, et al.
Published: (2025)
Neural Approximation of Generalized Voronoi Diagrams
by: Rigas, Panagiotis, et al.
Published: (2026)
by: Rigas, Panagiotis, et al.
Published: (2026)
Language Models Implement Simple Word2Vec-style Vector Arithmetic
by: Merullo, Jack, et al.
Published: (2023)
by: Merullo, Jack, et al.
Published: (2023)
The Geometry of the Set of Equivalent Linear Neural Networks
by: Shewchuk, Jonathan Richard, et al.
Published: (2024)
by: Shewchuk, Jonathan Richard, et al.
Published: (2024)
Rapid and Precise Topological Comparison with Merge Tree Neural Networks
by: Qin, Yu, et al.
Published: (2024)
by: Qin, Yu, et al.
Published: (2024)
Using Reinforcement Learning to Optimize the Global and Local Crossing Number
by: Brand, Timo, et al.
Published: (2025)
by: Brand, Timo, et al.
Published: (2025)
Extracting Complex Topology from Multivariate Functional Approximation: Contours, Jacobi Sets, and Ridge-Valley Graphs
by: Ma, Guanqun, et al.
Published: (2025)
by: Ma, Guanqun, et al.
Published: (2025)
Morphing Planar Graph Drawings via Orthogonal Box Drawings
by: Biedl, Therese, et al.
Published: (2024)
by: Biedl, Therese, et al.
Published: (2024)
Generating Diverse TSP Tours via a Combination of Graph Pointer Network and Dispersion
by: Yang, Hao-Tsung, et al.
Published: (2026)
by: Yang, Hao-Tsung, et al.
Published: (2026)
Hierarchical Neural Surfaces for 3D Mesh Compression
by: Pentapati, Sai Karthikey, et al.
Published: (2025)
by: Pentapati, Sai Karthikey, et al.
Published: (2025)
Bridging Graph Drawing and Dimensionality Reduction with Stochastic Stress Optimization
by: Hangan, Daniel, et al.
Published: (2026)
by: Hangan, Daniel, et al.
Published: (2026)
Minimum Enclosing Ball Synthetic Minority Oversampling Technique from a Geometric Perspective
by: Shangguan, Yi-Yang, et al.
Published: (2024)
by: Shangguan, Yi-Yang, et al.
Published: (2024)
Neural Snowflakes: Universal Latent Graph Inference via Trainable Latent Geometries
by: Borde, Haitz Sáez de Ocáriz, et al.
Published: (2023)
by: Borde, Haitz Sáez de Ocáriz, et al.
Published: (2023)
Filtration-Based Representation Learning for Temporal Graphs
by: Chowdhury, Samrik, et al.
Published: (2025)
by: Chowdhury, Samrik, et al.
Published: (2025)
EMP: Effective Multidimensional Persistence for Graph Representation Learning
by: Segovia-Dominguez, Ignacio, et al.
Published: (2024)
by: Segovia-Dominguez, Ignacio, et al.
Published: (2024)
Algorithm for Interpretable Graph Features via Motivic Persistent Cohomology
by: Maruyama, Yoshihiro
Published: (2025)
by: Maruyama, Yoshihiro
Published: (2025)
Estimate of the Neural Network Dimension using Algebraic Topology and Lie Theory
by: Melodia, Luciano, et al.
Published: (2020)
by: Melodia, Luciano, et al.
Published: (2020)
Min-$k$-planar Drawings of Graphs
by: Binucci, Carla, et al.
Published: (2023)
by: Binucci, Carla, et al.
Published: (2023)
Optimizing Kernel Discrepancies via Subset Selection
by: Chen, Deyao, et al.
Published: (2025)
by: Chen, Deyao, et al.
Published: (2025)
Differentiable Mapper For Topological Optimization Of Data Representation
by: Oulhaj, Ziyad, et al.
Published: (2024)
by: Oulhaj, Ziyad, et al.
Published: (2024)
On the Theoretical Expressive Power and the Design Space of Higher-Order Graph Transformers
by: Zhou, Cai, et al.
Published: (2024)
by: Zhou, Cai, et al.
Published: (2024)
ClusterGraph: a new tool for visualization and compression of multidimensional data
by: Dłotko, Paweł, et al.
Published: (2024)
by: Dłotko, Paweł, et al.
Published: (2024)
Linear-Size Neural Network Representation of Piecewise Affine Functions in $\mathbb{R}^2$
by: Zanotti, Leo
Published: (2025)
by: Zanotti, Leo
Published: (2025)
Topology-Preserving Neural Operator Learning via Hodge Decomposition
by: Zheng, Dongzhe, et al.
Published: (2026)
by: Zheng, Dongzhe, et al.
Published: (2026)
Towards Non-Euclidean Foundation Models: Advancing AI Beyond Euclidean Frameworks
by: Yang, Menglin, et al.
Published: (2025)
by: Yang, Menglin, et al.
Published: (2025)
tensorflow-riemopt: A Library for Optimization on Riemannian Manifolds
by: Smirnov, Oleg
Published: (2021)
by: Smirnov, Oleg
Published: (2021)
Parallel Graph Drawing Algorithm for Bipartite Planar Graphs
by: Jain, Naman
Published: (2024)
by: Jain, Naman
Published: (2024)
Closed-Form Training Dynamics Reveal Learned Features and Linear Structure in Word2Vec-like Models
by: Karkada, Dhruva, et al.
Published: (2025)
by: Karkada, Dhruva, et al.
Published: (2025)
Message Detouring: A Simple Yet Effective Cycle Representation for Expressive Graph Learning
by: Wei, Ziquan, et al.
Published: (2024)
by: Wei, Ziquan, et al.
Published: (2024)
Computing distances and means on manifolds with a metric-constrained Eikonal approach
by: Kelshaw, Daniel, et al.
Published: (2024)
by: Kelshaw, Daniel, et al.
Published: (2024)
Graph Neural Networks on Discriminative Graphs of Words
by: Abbahaddou, Yassine, et al.
Published: (2024)
by: Abbahaddou, Yassine, et al.
Published: (2024)
Graph Bayesian Optimization for Multiplex Influence Maximization
by: Yuan, Zirui, et al.
Published: (2024)
by: Yuan, Zirui, et al.
Published: (2024)
Graph-Based Nearest-Neighbor Search without the Spread
by: Giliberti, Jeff, et al.
Published: (2026)
by: Giliberti, Jeff, et al.
Published: (2026)
From Theory to Throughput: CUDA-Optimized APML for Large-Batch 3D Learning
by: Sharifipour, Sasan, et al.
Published: (2025)
by: Sharifipour, Sasan, et al.
Published: (2025)
Planar Stories of Graph Drawings: Algorithms and Experiments
by: Binucci, Carla, et al.
Published: (2025)
by: Binucci, Carla, et al.
Published: (2025)
Same Quality Metrics, Different Graph Drawings
by: van Wageningen, Simon, et al.
Published: (2025)
by: van Wageningen, Simon, et al.
Published: (2025)
Similar Items
-
CoRe-GD: A Hierarchical Framework for Scalable Graph Visualization with GNNs
by: Grötschla, Florian, et al.
Published: (2024) -
Size Should not Matter: Scale-invariant Stress Metrics
by: Ahmed, Reyan, et al.
Published: (2024) -
Graph Drawing Stress Model with Resistance Distances
by: Onoue, Yosuke
Published: (2025) -
Ironing the Graphs: Toward a Correct Geometric Analysis of Large-Scale Graphs
by: Naama, Saloua, et al.
Published: (2024) -
Topological Spatial Graph Coarsening
by: Calissano, Anna, et al.
Published: (2025)