HIPS / maxwells-daemonLinks
Fastidious accounting of entropy streams into and out of optimization and sampling algorithms.
☆33Updated 9 years ago
Alternatives and similar repositories for maxwells-daemon
Users that are interested in maxwells-daemon are comparing it to the libraries listed below
Sorting:
- Backpropagate derivatives through the Cholesky decomposition☆58Updated 5 years ago
- Python implementation of Markov Jump Hamiltonian Monte Carlo☆24Updated 8 years ago
- Reducing Reparameterization Gradient Variance code.☆33Updated 8 years ago
- Matlab code implementing Minimum Probability Flow Learning.☆69Updated 11 years ago
- Implementation of the reweighted wake-sleep machine learning algorithm☆42Updated 9 years ago
- Columbia Advanced Machine Learning Seminar☆24Updated 7 years ago
- Exponential Machines implementation☆42Updated 7 months ago
- Torch implementation of the Deep Network for Global Optimization (DNGO)☆51Updated 9 years ago
- Library of common tools for machine learning research.☆41Updated 7 years ago
- Topics on theoretical, mathematical aspects of DL☆72Updated 8 years ago
- Code for paper "Full-Capacity Unitary Recurrent Neural Networks"☆54Updated 8 years ago
- RNNprop☆36Updated 8 years ago
- This code accompanies the proximity variational inference paper.☆18Updated 6 years ago
- LaTeX package for randomizing author order based on a public seed.☆40Updated 10 years ago
- Deep GPs with GPy☆31Updated 9 years ago
- stochs: fast stochastic solvers for machine learning in C++ and Cython☆26Updated 3 years ago
- ☆11Updated 9 years ago
- Variational Bayes for NN in Torch7 (http://papers.nips.cc/paper/4329-practical-variational-inference-for-neural-networks.pdf)☆10Updated 10 years ago
- Implementation of Hamiltonian Monte Carlo using Google's TensorFlow☆46Updated 9 years ago
- Repo for a paper about constructing priors on very deep models.☆73Updated 9 years ago
- ☆20Updated 8 years ago
- An iterative neural autoregressive distribution estimator (NADE-K)☆26Updated 10 years ago
- A Newton ADMM based solver for Cone programming.☆39Updated 8 years ago
- Fast CPU implementations of several conditional probabilistic models☆37Updated 2 years ago
- NeurIPS 2016. Linear-time interpretable nonparametric two-sample test.☆64Updated 7 years ago
- Stochastic Gradient Riemannian Langevin Dynamics☆34Updated 10 years ago
- NeurIPS 2018. Linear-time model comparison tests.☆18Updated 5 years ago
- more composable than other neural network libraries☆42Updated 9 years ago
- Probabilistic Programming and Statistical Inference in PyTorch☆111Updated 8 years ago
- NeurIPS 2017 best paper. An interpretable linear-time kernel goodness-of-fit test.☆67Updated 6 years ago