dl-ml Goto Github PK

causally-regularized-learning

A method which takes advantage of causal features for classification

cdan

Code release for "Conditional Adversarial Domain Adaptation" (NIPS 2018)

cpp_primer_practice

搞定C++:punch:。C++ Primer 中文版第5版学习仓库，包括笔记和课后练习答案。

crowd-counting-using-pytorch

Pytorch based Crowd-Counting model to estimate the number of people in crowdy areas such as Stadium, Music festival etc.

csrnet-pytorch

CSRNet: Dilated Convolutional Neural Networks for Understanding the Highly Congested Scenes

deeplearning-500-questions

深度学习500问，以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述，以帮助自己及有需要的读者。 全书分为18个章节，50余万字。由于水平有限，书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作，联系[email protected] 版权所有，违权必究 Tan 2018.06

dl-uncertainty

"What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?", NIPS 2017 (unofficial code).

leetcode

LeetCode Solutions: A Record of My Problem Solving Journey.( leetcode题解，记录自己的leetcode解题之路。)

leetcode-1

leetcode code

leetcode-on-tag

tag sorted

mcmc

Collection of Monte Carlo (MC) and Markov Chain Monte Carlo (MCMC) algorithms applied on simple examples.

meanteacher-sntg-hybridnet

This is the Pytorch Re-Implementation of three Semi Supervised Classification method on Cifar-100 Dataset using ConvLarge Architecture

mixup_for_uda

Implementation of Adversarial Domain Adaptation with Domain Mixup (AAAI 2020 Oral).

my_coda

prml

PRML algorithms implemented in Python

probabilistic-models

Collection of probabilistic models and inference algorithms

pytorch-adda

A PyTorch implementation for Adversarial Discriminative Domain Adaptation

pytorch-ssim

pytorch structural similarity (SSIM) loss

sampyl

MCMC samplers for Bayesian estimation in Python, including Metropolis-Hastings, NUTS, and Slice

stable_linear_model_learning

The implementation and addtional material of AAAI2020 paper "Stable Learning via Sample Reweighting"