Pinned Repositories
autograd
Efficiently computes derivatives of NumPy code.
Spearmint
Spearmint Bayesian optimization codebase
basenji
Sequential regulatory activity predictions with deep convolutional neural networks.
jaspersnoek.github.io
jax
Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
Machine-March-Madness
Code for predicting the NCAA College Basketball 'March Madness' tournament
pix2pix-tensorflow
Tensorflow port of Image-to-Image Translation with Conditional Adversarial Nets https://phillipi.github.io/pix2pix/
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
threads
Threads for Lua and LuaJIT. Transparent exchange of data between threads is allowed thanks to torch serialization.
jax
Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
JasperSnoek's Repositories
JasperSnoek/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
JasperSnoek/Machine-March-Madness
Code for predicting the NCAA College Basketball 'March Madness' tournament
JasperSnoek/jax
Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
JasperSnoek/pix2pix-tensorflow
Tensorflow port of Image-to-Image Translation with Conditional Adversarial Nets https://phillipi.github.io/pix2pix/
JasperSnoek/basenji
Sequential regulatory activity predictions with deep convolutional neural networks.
JasperSnoek/jaspersnoek.github.io
JasperSnoek/threads
Threads for Lua and LuaJIT. Transparent exchange of data between threads is allowed thanks to torch serialization.