Picture for Yuichi Tanaka

Yuichi Tanaka

Time-Varying Graph Signal Estimation among Multiple Sub-Networks

Add code
Sep 17, 2024
Viaarxiv icon

Efficient Learning of Balanced Signed Graphs via Iterative Linear Programming

Add code
Sep 12, 2024
Viaarxiv icon

Constructing an Interpretable Deep Denoiser by Unrolling Graph Laplacian Regularizer

Add code
Sep 10, 2024
Figure 1 for Constructing an Interpretable Deep Denoiser by Unrolling Graph Laplacian Regularizer
Figure 2 for Constructing an Interpretable Deep Denoiser by Unrolling Graph Laplacian Regularizer
Figure 3 for Constructing an Interpretable Deep Denoiser by Unrolling Graph Laplacian Regularizer
Figure 4 for Constructing an Interpretable Deep Denoiser by Unrolling Graph Laplacian Regularizer
Viaarxiv icon

Edge Sampling of Graphs: Graph Signal Processing Approach With Edge Smoothness

Add code
Jul 14, 2024
Figure 1 for Edge Sampling of Graphs: Graph Signal Processing Approach With Edge Smoothness
Figure 2 for Edge Sampling of Graphs: Graph Signal Processing Approach With Edge Smoothness
Figure 3 for Edge Sampling of Graphs: Graph Signal Processing Approach With Edge Smoothness
Figure 4 for Edge Sampling of Graphs: Graph Signal Processing Approach With Edge Smoothness
Viaarxiv icon

Physics-Inspired Synthesized Underwater Image Dataset

Add code
Apr 05, 2024
Viaarxiv icon

Lossy Compression of Adjacency Matrices by Graph Filter Banks

Add code
Feb 05, 2024
Figure 1 for Lossy Compression of Adjacency Matrices by Graph Filter Banks
Figure 2 for Lossy Compression of Adjacency Matrices by Graph Filter Banks
Figure 3 for Lossy Compression of Adjacency Matrices by Graph Filter Banks
Figure 4 for Lossy Compression of Adjacency Matrices by Graph Filter Banks
Viaarxiv icon

Optimizing $k$ in $k$NN Graphs with Graph Learning Perspective

Add code
Jan 16, 2024
Viaarxiv icon

Clustering of Time-Varying Graphs Based on Temporal Label Smoothness

Add code
May 11, 2023
Viaarxiv icon

Attention-based Graph Convolution Fusing Latent Structures and Multiple Features for Graph Neural Networks

Add code
Mar 03, 2023
Figure 1 for Attention-based Graph Convolution Fusing Latent Structures and Multiple Features for Graph Neural Networks
Figure 2 for Attention-based Graph Convolution Fusing Latent Structures and Multiple Features for Graph Neural Networks
Figure 3 for Attention-based Graph Convolution Fusing Latent Structures and Multiple Features for Graph Neural Networks
Figure 4 for Attention-based Graph Convolution Fusing Latent Structures and Multiple Features for Graph Neural Networks
Viaarxiv icon

Dynamic Sensor Placement Based on Graph Sampling Theory

Add code
Nov 08, 2022
Figure 1 for Dynamic Sensor Placement Based on Graph Sampling Theory
Figure 2 for Dynamic Sensor Placement Based on Graph Sampling Theory
Figure 3 for Dynamic Sensor Placement Based on Graph Sampling Theory
Figure 4 for Dynamic Sensor Placement Based on Graph Sampling Theory
Viaarxiv icon