Providing reproducibility in deep learning frameworks
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Updated
May 13, 2024 - Python
Providing reproducibility in deep learning frameworks
Named dimensions and indexing for julia arrays and other data
A scheduler for GPU/CPU tasks
HPC solver for nonlinear optimization problems
Graphics Processing Unit (GPU) Architecture Guide
Pitch-shift audio clips quickly with PyTorch (CUDA supported)! Additional utilities for searching efficient transformations are included.
Bright Wire is an open source machine learning library for .NET with GPU support (via CUDA)
Python Suite for Advanced General Ensemble Simulations
GPU-accelerated Quantum ESPRESSO using CUDA FORTRAN
Computer Vision And Neural Network with Xamarin
Zero-dependency FFmpeg-based batch framework for repetitive and bulk high-quality transcoding in one click
A Folding@Home Docker container with GPU support
Time-stretch audio clips quickly with PyTorch (CUDA supported)! Additional utilities for searching efficient transformations are included.
"A neural network to rule them all, a neural network to find them, a neural network to bring them all and verify if is you !!" (Face recognition tool)
Add GPU support to your Singularity container!
SERVER: Multi-modal Speech Emotion Recognition using Transformer-based and Vision-based Embeddings
Matrix-Vector Library Designed for Neural Network Construction. cuda (gpu) support, openmp (multithreaded cpu) support, partial support of BLAS, expression template based implementation PTX code generation identical to hand written kernels, and support for auto-differentiation
C++ and Python implementation of a automatic system for pedestrian detection at night using far infrared visual information based on convolutional neural networks.
Fast CPU and GPU Python implementations of Improved Kernel PLS by Dayal and MacGregor (1997) and Shortcutting Cross-Validation by Engstrøm (2024).
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