Aesara is a Python library for defining, optimizing, and efficiently evaluating mathematical expressions involving multi-dimensional arrays.
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Updated
Sep 5, 2024 - Python
Aesara is a Python library for defining, optimizing, and efficiently evaluating mathematical expressions involving multi-dimensional arrays.
Stretching GPU performance for GEMMs and tensor contractions.
A python library for quantum information and many-body calculations including tensor networks.
Distributed tensors and Machine Learning framework with GPU and MPI acceleration in Python
Tensor Network Learning with PyTorch
Type annotations and dynamic checking for a tensor's shape, dtype, names, etc.
Performance evaluation of nearest neighbor search using Vespa, Elasticsearch and Open Distro for Elasticsearch K-NN
Python Tensor Toolbox
Deep learning for spiking neural networks
CP-APR Tensor Decomposition with PyTorch backend. pyCP_APR can perform non-negative Poisson Tensor Factorization on GPU, and includes an interface for anomaly detection using the extracted latent patterns.
Easy visualization and evaluation of matrix and tensor factorization models
Database approach for generating near-roofline Einstein Summation kernels.
Sequence models implementation in Tensorflow.
TensorHue is a Python library that allows you to visualize tensors right in your console, making understanding and debugging tensor contents easier.
Tensor Extraction of Latent Features (T-ELF). Within T-ELF's arsenal are non-negative matrix and tensor factorization solutions, equipped with automatic model determination (also known as the estimation of latent factors - rank) for accurate data modeling. Our software suite encompasses cutting-edge data pre-processing and post-processing modules.
SIR model parameter estimation using a novel algorithm for differentiated uniformization.
AugStatic - A Light-Weight Image Augmentation Library
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