sphinxteam / DukeLecture2018
Set of Lecture at Duke in 2018 by Lenka Zdeborova and Florent Krzakala "Statistical Physics For Optimization and Learning"
☆16Updated 5 years ago
Alternatives and similar repositories for DukeLecture2018:
Users that are interested in DukeLecture2018 are comparing it to the libraries listed below
- Combining smooth constraint for building DAG with normalizing flow in order to replace autoregressive transformations while keeping tract…☆45Updated last year
- A Python package for efficient optimisation of real-space renormalization group transformations using Tensorflow.☆28Updated last month
- Neural likelihood-free methods in PyTorch.☆39Updated 5 years ago
- Sequential Neural Likelihood☆39Updated 5 years ago
- Conditional density estimation with neural networks☆30Updated 2 months ago
- Riemannian Optimization Using JAX☆48Updated last year
- Normalizing Flows using JAX☆83Updated last year
- Lightweight library of stochastic gradient MCMC algorithms written in JAX.☆102Updated last year
- Code used for experiments in https://arxiv.org/abs/2008.08601☆19Updated 3 years ago
- RKHS feature vectors, operators, and statistical models using JAX for automatic differentiation☆8Updated 3 years ago
- INTRODUCTION TO MACHINE LEARNING: An introductory practical course by Florent Krzakala and Antoine Baker☆14Updated 5 years ago
- ☆112Updated 7 years ago
- Deterministic particle dynamics for simulating Fokker-Planck probability flows☆24Updated 2 years ago
- Code for efficiently sampling functions from GP(flow) posteriors☆71Updated 4 years ago
- A generic interface for linear algebra backends☆73Updated last month
- Simulation-based inference benchmark☆97Updated 2 months ago
- Pytorch source code for arXiv paper Neural Network Renormalization Group, a generative model using variational renormalization group and …☆79Updated 5 years ago
- Continuous-time gradient flow for generative modeling and variational inference☆30Updated 6 years ago
- Exponential families for JAX☆63Updated this week
- Turning SymPy expressions into JAX functions☆44Updated 4 years ago
- Bayesian inference with Python and Jax.☆32Updated 2 years ago
- Code for Gaussian Score Matching Variational Inference☆33Updated last month
- An ultra-lightweight JAX implementation of sparse Gaussian processes via pathwise sampling.☆22Updated 4 years ago
- Implementation of approximate free-energy minimization in PyTorch☆19Updated 3 years ago
- Tutorials and sampling algorithm comparisons☆72Updated this week
- ☆50Updated 2 years ago
- Hamiltonian Dynamics with Non-Newtonian Momentum for Rapid Sampling☆36Updated 3 years ago
- Matrix-free linear algebra in JAX.☆116Updated 2 months ago
- Jupyter notebooks for "A high-bias, low-variance introduction to Machine Learning for physicists"☆192Updated 3 years ago
- Repository for DTU Special Course, focusing on Variational Inference using Normalizing Flows (VINF). Supervised by Michael Riis Andersen☆25Updated 4 years ago