Picture for Zhuo Feng

Zhuo Feng

SGM-PINN: Sampling Graphical Models for Faster Training of Physics-Informed Neural Networks

Add code
Jul 10, 2024
Viaarxiv icon

Geodesic Distance Between Graphs: A Spectral Metric for Assessing the Stability of Graph Neural Networks

Add code
Jun 15, 2024
Figure 1 for Geodesic Distance Between Graphs: A Spectral Metric for Assessing the Stability of Graph Neural Networks
Figure 2 for Geodesic Distance Between Graphs: A Spectral Metric for Assessing the Stability of Graph Neural Networks
Figure 3 for Geodesic Distance Between Graphs: A Spectral Metric for Assessing the Stability of Graph Neural Networks
Figure 4 for Geodesic Distance Between Graphs: A Spectral Metric for Assessing the Stability of Graph Neural Networks
Viaarxiv icon

Researchy Questions: A Dataset of Multi-Perspective, Decompositional Questions for LLM Web Agents

Add code
Feb 27, 2024
Viaarxiv icon

inGRASS: Incremental Graph Spectral Sparsification via Low-Resistance-Diameter Decomposition

Add code
Feb 26, 2024
Figure 1 for inGRASS: Incremental Graph Spectral Sparsification via Low-Resistance-Diameter Decomposition
Figure 2 for inGRASS: Incremental Graph Spectral Sparsification via Low-Resistance-Diameter Decomposition
Figure 3 for inGRASS: Incremental Graph Spectral Sparsification via Low-Resistance-Diameter Decomposition
Figure 4 for inGRASS: Incremental Graph Spectral Sparsification via Low-Resistance-Diameter Decomposition
Viaarxiv icon

SAGMAN: Stability Analysis of Graph Neural Networks on the Manifolds

Add code
Feb 21, 2024
Figure 1 for SAGMAN: Stability Analysis of Graph Neural Networks on the Manifolds
Figure 2 for SAGMAN: Stability Analysis of Graph Neural Networks on the Manifolds
Figure 3 for SAGMAN: Stability Analysis of Graph Neural Networks on the Manifolds
Figure 4 for SAGMAN: Stability Analysis of Graph Neural Networks on the Manifolds
Viaarxiv icon

A Topology-aware Graph Coarsening Framework for Continual Graph Learning

Add code
Jan 05, 2024
Viaarxiv icon

SF-SGL: Solver-Free Spectral Graph Learning from Linear Measurements

Add code
Feb 09, 2023
Figure 1 for SF-SGL: Solver-Free Spectral Graph Learning from Linear Measurements
Figure 2 for SF-SGL: Solver-Free Spectral Graph Learning from Linear Measurements
Figure 3 for SF-SGL: Solver-Free Spectral Graph Learning from Linear Measurements
Figure 4 for SF-SGL: Solver-Free Spectral Graph Learning from Linear Measurements
Viaarxiv icon

HyperEF: Spectral Hypergraph Coarsening by Effective-Resistance Clustering

Add code
Oct 26, 2022
Figure 1 for HyperEF: Spectral Hypergraph Coarsening by Effective-Resistance Clustering
Figure 2 for HyperEF: Spectral Hypergraph Coarsening by Effective-Resistance Clustering
Figure 3 for HyperEF: Spectral Hypergraph Coarsening by Effective-Resistance Clustering
Figure 4 for HyperEF: Spectral Hypergraph Coarsening by Effective-Resistance Clustering
Viaarxiv icon

GARNET: Reduced-Rank Topology Learning for Robust and Scalable Graph Neural Networks

Add code
Feb 01, 2022
Figure 1 for GARNET: Reduced-Rank Topology Learning for Robust and Scalable Graph Neural Networks
Figure 2 for GARNET: Reduced-Rank Topology Learning for Robust and Scalable Graph Neural Networks
Figure 3 for GARNET: Reduced-Rank Topology Learning for Robust and Scalable Graph Neural Networks
Figure 4 for GARNET: Reduced-Rank Topology Learning for Robust and Scalable Graph Neural Networks
Viaarxiv icon

HyperSF: Spectral Hypergraph Coarsening via Flow-based Local Clustering

Add code
Aug 17, 2021
Figure 1 for HyperSF: Spectral Hypergraph Coarsening via Flow-based Local Clustering
Figure 2 for HyperSF: Spectral Hypergraph Coarsening via Flow-based Local Clustering
Figure 3 for HyperSF: Spectral Hypergraph Coarsening via Flow-based Local Clustering
Figure 4 for HyperSF: Spectral Hypergraph Coarsening via Flow-based Local Clustering
Viaarxiv icon