Constrained optimization toolkit for PyTorch
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Updated
Mar 1, 2022 - Python
Constrained optimization toolkit for PyTorch
Spectral Tensor Train Parameterization of Deep Learning Layers
Efficient Householder Transformation in PyTorch
Plotting the loss of Orthogonality of a matrix at each iteration step due to four different methods of Orthogonalization
A set of codes in MATLAB for ODE reconstruction using least-square method
Vectors, matrices, linear equations, Gaussian elimination, vector geometry with dot product and vector product, determinants, vector spaces, linear independence, bases, change of basis, linear transformations, the least-squares method, eigenvalues, eigenvectors, quadratic forms, orthogonality, inner-product space, Gram-Schmidt's method.
Model reduction of 2D diffusion equation
Basic and advanced linear algebra and numerical problems, numerical algorithms, and techniques with multiple applications in the field of Computer Science.
TensorFlow implementation of differentiable LQ matrix decomposition for all matrix orders.
A small C-library for Linear Algebra functions that do complex matrix calculations.
[IEEE Access 2022] Revisiting Orthogonality Regularization: A Study for Convolutional Neural Networks in Image Classification
Co-clustering algorithms can seek homogeneous sub-matrices into a dyadic data matrix, such as a document-word matrix.
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