h-jia Goto Github PK

keras-gp

Keras + Gaussian Processes: Learning scalable deep and recurrent kernels.

keras-shufflenetv2

Keras implementation of ShuffleNet V2

keras_shufflenetv2

keras_shufflenetv2

keygen

key generation

kinetics_i3d_pytorch

Inflated i3d network with inception backbone, weights transfered from tensorflow

librealsense

Intel® RealSense™ SDK

lihang

Statistical learning methods, 统计学习方法(第2版)[李航] [笔记, 代码, notebook, 参考文献, Errata, lihang]

lottery-ticket-hypothesis

A reimplementation of "The Lottery Ticket Hypothesis" (Frankle and Carbin) on MNIST.

marrnet

MarrNet: 3D Shape Reconstruction via 2.5D Sketches

matlabsublime

mdan

Demo code for the MDAN paper.

minimalrl

Implementations of basic RL algorithms with minimal lines of codes! (pytorch based)

mlapp_cn_code

《Machine Learning: A Probabilistic Perspective》（Kevin P. Murphy）中文翻译和书中算法的Python实现。

mm-distillnet

PyTorch code for training MM-DistillNet for multimodal knowledge distillation. http://rl.uni-freiburg.de/research/multimodal-distill

moving_average

ms_ssim_pytorch

ms_ssim loss function implemented in pytorch

mt-dnn

Multi-Task Deep Neural Networks for Natural Language Understanding

nasp-codes

neural-processes

PyTorch implementation of Neural Processes

neuralweightvirtualization

[MobiSys 2020] Fast and Scalable In-memory Deep Multitask Learning via Neural Weight Virtualization

nn-transfer

Convert trained PyTorch models to Keras, and the other way around

nostalgicadam-nosadam

Nostalgic Adam: Weighting more of the past gradients when designing the adaptive learning rate

numpy-ml

Machine learning, in numpy

pamap2-physical-activity-monitoring-data-analysis-and-ml

Data Analysis and Machine Learning on Physical monitoring data

papyrus

pc-darts

PC-DARTS:Partial Channel Connections for Memory-Efficient Differentiable Architecture Search

pdf-toc-creator

为PDF文档创建目录

phd_thesis_markdown

Template for writing a PhD thesis in Markdown

plant_disease_experiments

A project to train and evaluate different dnn models for plant disease detection problem, tackle the problem of scarce real-life representative data, experiment with different generative networks and generate more plant leaf image data and implement segmentation pipeline to avoid miss-classification due to unwanted input

plotneuralnet

Latex code for making neural networks diagrams