Constrained optimization toolkit for PyTorch
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Updated
Mar 1, 2022 - Python
Constrained optimization toolkit for PyTorch
Efficient Householder Transformation in PyTorch
Spectral Tensor Train Parameterization of Deep Learning Layers
[IEEE Access 2022] Revisiting Orthogonality Regularization: A Study for Convolutional Neural Networks in Image Classification
Plotting the loss of Orthogonality of a matrix at each iteration step due to four different methods of Orthogonalization
TensorFlow implementation of differentiable LQ matrix decomposition for all matrix orders.
Co-clustering algorithms can seek homogeneous sub-matrices into a dyadic data matrix, such as a document-word matrix.
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
A set of codes in MATLAB for ODE reconstruction using least-square method
Basic and advanced linear algebra and numerical problems, numerical algorithms, and techniques with multiple applications in the field of Computer Science.
A small C-library for Linear Algebra functions that do complex matrix calculations.
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