Keyphrases
Convolutional Neural Network
100%
Multigrid
67%
Graph Neural Network
55%
Inverse Problem
42%
Helmholtz Equation
39%
Number of Parameters
32%
Partial Differential Equations
31%
Computational Cost
28%
In-channel
26%
Graph Convolutional Network
26%
Full-waveform Inversion
26%
U-Net
25%
Node Classification
24%
Traveltime Tomography
21%
Convolution Operator
21%
Numerical Experiments
20%
Sparse Inverse Covariance Estimation
19%
Least Absolute Shrinkage and Selection Operator (LASSO)
19%
Numerical Results
19%
Neural Network Architecture
19%
Shrinkage Algorithm
17%
Iterated Shrinkage
17%
Penalized Least Squares
17%
Least-squares Minimization
17%
Markov Chain
17%
Gradient-free
17%
Quantized Neural Networks
17%
Hessian
17%
Iterative Hard Thresholding Algorithm
17%
Graphical Lasso
17%
Bit Allocation
17%
Deep Convolutional Neural Network (deep CNN)
17%
Deep Learning
17%
Semantic Segmentation
17%
Coarse Grid
17%
Neural Network
16%
Deep Neural Network
15%
Estimation Problem
15%
Sparsity Pattern
15%
Computational Complexity
14%
Shifted Laplacian
14%
Multigrid Solver
14%
L1 Regularization
13%
Quadratic Approximation
13%
Sparse Solution
13%
Residual Network
12%
Travel Time
12%
Smoothed Aggregation
11%
Regularizer
11%
Point Source
11%
Mathematics
Partial Differential Equation
49%
Helmholtz Equation
49%
Convolutional Neural Network
38%
Covariance
35%
Regularization
32%
Numerical Experiment
30%
Lasso Regression
29%
Matrix (Mathematics)
29%
Laplace Operator
28%
Convolution
26%
Quadratic Approximation
22%
Real Data
22%
Approximates
22%
Computational Cost
20%
Multigrid Method
19%
Discretization
17%
Markov Chain
17%
Shrinkage Approach
17%
Quasi-Newton Method
17%
Synthetic Data
17%
Thresholding
17%
Least Square
17%
Source Point
17%
Deep Learning Method
17%
Local Minimum
13%
High-Frequency Data
11%
Dimensional Problem
11%
Gaussian Distribution
11%
Linear System
11%
Numerical Solution
11%
Neural Network
10%
Markov Random Fields
9%
Deep Learning
8%
Priori Information
8%
Noisy Data
8%
Stochastic Matrix
8%
Variational Formulation
8%
Posed Problem
8%
Graph Laplacian
8%
Logistic Regression
8%
Nonlinear Model
8%
Input Feature
8%
Residual Network
8%
Null
8%
Scalar
8%
Systems of Linear Equation
8%
Nonlinear
8%
Differential Operator
8%
Convolution Operator
8%
Wavelet
8%
Computer Science
Convolutional Neural Network
82%
Graph Neural Network
73%
Node Classification
34%
Partial Differential Equation
34%
Selection Operator
26%
Preconditioner
26%
Quantization (Signal Processing)
26%
Neural Network Architecture
23%
Graph Convolutional Network
21%
Neural Network
21%
Deep Convolutional Neural Networks
20%
Residual Neural Network
18%
Soft Thresholding
17%
Quasi-Newton Method
17%
Approximation (Algorithm)
17%
Hardware Accelerator
17%
Deep Learning Method
17%
Image Segmentation
16%
Deep Neural Network
13%
Computational Cost
12%
Point Cloud
11%
Inverse Problem
11%
Sparsity
10%
Computational Complexity
10%
Machine Learning
10%
Process Optimization
10%
Image Classification
9%
Sparsity Pattern
9%
Superpixel Segmentation
8%
Search Space
8%
Tool Implementation
8%
Debugging Tool
8%
Positional Encoding
8%
Mixed-Precision Neural Networks
8%
Performance Optimization
8%
Computer Vision Task
8%
level-set method
8%
Diffusion Model
8%
Biological Difference
8%
Partial Differential Equation
8%
Parameter Estimation
8%
Receptive Field
8%
Convolutional Neural Network
8%
Medical Imaging
6%
Propagation Step
5%
Objective Function
5%
Gaussian Mixture Model
5%
Channel Approach
5%
