Pinned Repositories
CalibrationNN
Model Calibration with Neural Networks
CppAD
Development is done here and mirrored on COIN-OR
gym
A toolkit for developing and comparing reinforcement learning algorithms.
keras
Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on Theano and TensorFlow.
keras-rl
Deep Reinforcement Learning for Keras.
py-optim
Gradient-based optimization algorithms in Python
pymc3
Probabilistic Programming in Python: Bayesian Modeling and Probabilistic Machine Learning with Theano
QuantLib
The QuantLib C++ library
quantlib-old
The QuantLib C++ library and extensions
QuantLib-SWIG
The QuantLib extension modules
Andres-Hernandez's Repositories
Andres-Hernandez/CalibrationNN
Model Calibration with Neural Networks
Andres-Hernandez/QuantLib
The QuantLib C++ library
Andres-Hernandez/CppAD
Development is done here and mirrored on COIN-OR
Andres-Hernandez/gym
A toolkit for developing and comparing reinforcement learning algorithms.
Andres-Hernandez/keras
Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on Theano and TensorFlow.
Andres-Hernandez/keras-rl
Deep Reinforcement Learning for Keras.
Andres-Hernandez/py-optim
Gradient-based optimization algorithms in Python
Andres-Hernandez/pymc3
Probabilistic Programming in Python: Bayesian Modeling and Probabilistic Machine Learning with Theano
Andres-Hernandez/quantlib-old
The QuantLib C++ library and extensions
Andres-Hernandez/QuantLib-SWIG
The QuantLib extension modules
Andres-Hernandez/spearmint
Spearmint is a package to perform Bayesian optimization according to the algorithms outlined in the paper: Practical Bayesian Optimization of Machine Learning Algorithms. Jasper Snoek, Hugo Larochelle and Ryan P. Adams. Advances in Neural Information Processing Systems, 2012
Andres-Hernandez/Spoon-Knife
This repo is for demonstration purposes only.
Andres-Hernandez/tapescript
AAD class library with tape compression, optimized for Monte Carlo and quant finance
Andres-Hernandez/tensorflow
Computation using data flow graphs for scalable machine learning
Andres-Hernandez/torchdiffeq
Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.