yalechang
interested in machine learning and its applications in improving healthcare
Philips Research North AmericaCambridge MA
Pinned Repositories
adversarial-robustness-toolbox
This is a library dedicated to adversarial machine learning. Its purpose is to allow rapid crafting and analysis of attacks and defense methods for machine learning models. The Adversarial Robustness Toolbox provides an implementation for many state-of-the-art methods for attacking and defending classifiers. https://developer.ibm.com/code/open/projects/adversarial-robustness-toolbox/
computer_vision
COPDGene
Code for the COPDGene project(http://www.copdgene.org/)
fast_rgf
Multi-core implementation of Regularized Greedy Forest
imbalanced-learn
Python module to perform under sampling and over sampling with various techniques.
MCVC
ICML 2017: Multiple Clustering Views from Multiple Uncertain Experts
multiview
sampling
Implementation of various Sampling Algorithms for Bayesian Inference
symnmf
yalechang.github.io
Homepage
yalechang's Repositories
yalechang/fast_rgf
Multi-core implementation of Regularized Greedy Forest
yalechang/aas
Code to accompany Advanced Analytics with Spark from O'Reilly Media
yalechang/adversarial-autoencoder
A Lasagne and Theano implementation of the paper Alireza Makhzani, Jonathon Shlens, Navdeep Jaitly, and Ian Goodfellow.
yalechang/Awesome-Linux-Software
🐧 A curated list of awesome applications, softwares, tools and other materials for Linux distros.
yalechang/awesome-machine-learning
A curated list of awesome Machine Learning frameworks, libraries and software.
yalechang/Bayesic
Probabilistic programming for large datasets, via stochastic variational inference
yalechang/caret
caret (Classification And Regression Training) R package that contains misc functions for training and plotting classification and regression models
yalechang/causalTree
Working repository for Causal Tree and extensions
yalechang/cfrnet
Counterfactual Regression
yalechang/data-science-blogs
A curated list of data science blogs
yalechang/data-science-from-scratch
code for Data Science From Scratch book
yalechang/dcgan_code
Deep Convolutional Generative Adversarial Networks
yalechang/DeepLearningBook
MIT Deep Learning Book in PDF format
yalechang/edward
A library for probabilistic modeling, inference, and criticism. Deep generative models, variational inference. Runs on TensorFlow.
yalechang/epibook.github.io
Publishes to Github Pages
yalechang/incubator-systemml
Mirror of Apache SystemML (Incubating)
yalechang/java_projects
Study Java Programming
yalechang/JRNN
LSTM and GRU in JAVA
yalechang/k2abc
K2-ABC: Approximate Bayesian Computation with Kernel Embeddings
yalechang/keystone
Simplifying robust end-to-end machine learning on Apache Spark.
yalechang/minpy
Pure numpy practice with third party operator Integration
yalechang/parmesan
Variational and semi-supervised neural network toppings for Lasagne
yalechang/pixel-rnn-tensorflow
in progress
yalechang/PowerGraph
PowerGraph: A framework for large-scale machine learning and graph computation.
yalechang/pybind11
Seamless operability between C++11 and Python
yalechang/rnn-theano
RNN(LSTM, GRU) in Theano with mini-batch training; character-level language models in Theano
yalechang/SparkADMM
Generic Implementation of Consensus ADMM over Spark
yalechang/Stein-Variational-Gradient-Descent
code for the paper "Stein Variational Gradient Descent (SVGD): A General Purpose Bayesian Inference Algorithm"
yalechang/vae-experiments
Code for some of the experiments I did with variational autoencoders on multi-modality and atari video prediction. Atari video prediction is work-in-progress.
yalechang/warped-mixtures
Code for density estimation with nonparametric cluster shapes.