hma02

cublasHgemm-P100

Code for testing the native float16 matrix multiplication performance on Tesla P100 and V100 GPU based on cublasHgemm

cublasgemm-benchmark

code for benchmarking GPU performance based on cublasSgemm and cublasHgemm

deeplearnjs-practice

Pure javascript deeplearnjs demos

GAN-evaluation

AllanMa

AllanMa's HomePage

Ueval

Evaluate sample qualities of GANs in a browser.

code-samples

Source code examples from the Parallel Forall Blog

convnetjs

Deep Learning in Javascript. Train Convolutional Neural Networks (or ordinary ones) in your browser.

deep-dashboard

Deep Dashboard: Machine Learning Training Visualizer

deeplearnjs

Hardware-accelerated deep learning // machine learning // NumPy library for the web.

Delving-deep-into-GANs

A curated, quasi-exhaustive list of state-of-the-art publications and resources about Generative Adversarial Networks (GANs) and their applications.

dl4j-examples

Deeplearning4j Examples (DL4J, DL4J Spark, DataVec)

fcn.berkeleyvision.org

Fully Convolutional Networks for Semantic Segmentation by Jonathan Long*, Evan Shelhamer*, and Trevor Darrell. CVPR 2015 and PAMI 2016.

flask-celery-example

This repository contains the example code for my blog article Using Celery with Flask.

GA3C

Benchmarking code of Hybrid CPU/GPU implementation of the A3C algorithm for deep reinforcement learning.

Human-detection-and-Tracking

Human-detection-and-Tracking

improved_wgan_training

Code for reproducing experiments in "Improved Training of Wasserstein GANs"

Lasagne

Lightweight library to build and train neural networks in Theano

libgpuarray

Library to manipulate tensors on the GPU.

pytorch-CycleGAN-and-pix2pix

Image-to-image translation in PyTorch (e.g. horse2zebra, edges2cats, and more)

pytorch-generative-model-collections

Collection of generative models in Pytorch version.

rmate-python

Python implementation of rmate for TextMate 2

Sabaki

An elegant Go/Baduk/Weiqi board and SGF editor for a more civilized age.

seg-practice-caffe

Theano

Theano is a Python library that allows you to define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently. It can use GPUs and perform efficient symbolic differentiation.

Theano-MPI

MPI Parallel framework for training deep learning models built in Theano

TorchMPI

Implements a message passing interface (MPI) wrapper that makes it easy to do massively parallel computations inside the Torch deep-learning framework.

useful-commands

Some personally collected useful bash commands for reuse

wide-resnet

Implementation of Wide Residual Networks in Keras

wide_resnets_keras

Keras implementation + pretrained weights for "Wide Residual Networks"