hma02

cs231n.github.io

Public facing notes page

cublasgemm-benchmark

code for benchmarking GPU performance based on cublasSgemm and cublasHgemm

cublasHgemm-P100

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

deeplearnjs-practice

Pure javascript deeplearnjs demos

GAN-evaluation

Theano

Theano was a Python library that allows you to define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently. It is being continued as PyTensor: www.github.com/pymc-devs/pytensor

Theano-MPI

MPI Parallel framework for training deep learning models built in Theano

theano_alexnet

Theano-based Alexnet

hma02/cublasHgemm-P100

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

hma02/cublasgemm-benchmark

code for benchmarking GPU performance based on cublasSgemm and cublasHgemm

hma02/deeplearnjs-practice

Pure javascript deeplearnjs demos

hma02/GAN-evaluation

hma02/AllanMa

AllanMa's HomePage

hma02/Ueval

Evaluate sample qualities of GANs in a browser.

hma02/code-samples

Source code examples from the Parallel Forall Blog

hma02/convnetjs

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

hma02/deep-dashboard

Deep Dashboard: Machine Learning Training Visualizer

hma02/deeplearnjs

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

hma02/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.

hma02/dl4j-examples

Deeplearning4j Examples (DL4J, DL4J Spark, DataVec)

hma02/fcn.berkeleyvision.org

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

hma02/flask-celery-example

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

hma02/GA3C

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

hma02/Human-detection-and-Tracking

Human-detection-and-Tracking

hma02/improved_wgan_training

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

hma02/Lasagne

Lightweight library to build and train neural networks in Theano

hma02/libgpuarray

Library to manipulate tensors on the GPU.

hma02/pytorch-CycleGAN-and-pix2pix

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

hma02/pytorch-generative-model-collections

Collection of generative models in Pytorch version.

hma02/rmate-python

Python implementation of rmate for TextMate 2

hma02/Sabaki

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

hma02/seg-practice-caffe

hma02/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.

hma02/Theano-MPI

MPI Parallel framework for training deep learning models built in Theano

hma02/TorchMPI

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

hma02/useful-commands

Some personally collected useful bash commands for reuse

hma02/wide-resnet

Implementation of Wide Residual Networks in Keras

hma02/wide_resnets_keras

Keras implementation + pretrained weights for "Wide Residual Networks"