Pinned Repositories
autograd
Efficiently computes derivatives of numpy code.
chinese_chess_in_OCaml
CS 3110 Final Project
conda-moe
conda recipe for MOE (A global, black box optimization engine for real world metric optimization.)
Cornell-MOE
A Python library for the state-of-the-art Bayesian optimization algorithms, with the core implemented in C++.
darts
Differentiable architecture search for convolutional and recurrent networks
DeepLearningImplementations
Implementation of recent Deep Learning papers
demandForecast
HPOlib
HPOlib is a hyperparameter optimization library. It provides a common interface to three state of the art hyperparameter optimization packages: SMAC, spearmint and hyperopt. This package is discontinued, please read the longer note in the info box below.
TensorFlow-Examples
TensorFlow Tutorial and Examples for beginners
TwoStep-BayesOpt
NeurIPS 2019 Paper
wujian16's Repositories
wujian16/Cornell-MOE
A Python library for the state-of-the-art Bayesian optimization algorithms, with the core implemented in C++.
wujian16/TwoStep-BayesOpt
NeurIPS 2019 Paper
wujian16/chinese_chess_in_OCaml
CS 3110 Final Project
wujian16/DeepLearningImplementations
Implementation of recent Deep Learning papers
wujian16/TensorFlow-Examples
TensorFlow Tutorial and Examples for beginners
wujian16/autograd
Efficiently computes derivatives of numpy code.
wujian16/conda-moe
conda recipe for MOE (A global, black box optimization engine for real world metric optimization.)
wujian16/darts
Differentiable architecture search for convolutional and recurrent networks
wujian16/demandForecast
wujian16/HPOlib
HPOlib is a hyperparameter optimization library. It provides a common interface to three state of the art hyperparameter optimization packages: SMAC, spearmint and hyperopt. This package is discontinued, please read the longer note in the info box below.
wujian16/hyperband
Tuning hyperparams fast with Hyperband
wujian16/hypergrad
Exploring differentiation with respect to hyperparameters
wujian16/keras
Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on Theano or TensorFlow.
wujian16/learning-to-learn
Learning to Learn in TensorFlow
wujian16/Neural-Net-Bayesian-Optimization
We use a modified neural network instead of Gaussian process for Bayesian optimization.
wujian16/OpenAeroStruct
OpenAeroStruct is a lightweight tool to perform aerostructural optimization using OpenMDAO.
wujian16/reinforcement-learning-an-introduction
Python implementation of Reinforcement Learning: An Introduction
wujian16/RestaurantRevenuePrediction_ORIE6125
The Final Project of ORIE 6125
wujian16/RoBO
RoBO: a Robust Bayesian Optimization framework
wujian16/scikit-learn
scikit-learn: machine learning in Python
wujian16/sgmcmc
Stochastic Gradient MCMC algorithms implemented in theano (and autograd)
wujian16/taKG
supplementary materials for the taKG paper published at UAI 2019
wujian16/tensorflow
Computation using data flow graphs for scalable machine learning
wujian16/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.