sphinxteam / DukeLecture2018
Set of Lecture at Duke in 2018 by Lenka Zdeborova and Florent Krzakala "Statistical Physics For Optimization and Learning"
☆16Updated 4 years ago
Related projects ⓘ
Alternatives and complementary repositories for DukeLecture2018
- Sequential Neural Likelihood☆38Updated 5 years ago
- Deterministic particle dynamics for simulating Fokker-Planck probability flows☆24Updated last year
- Neural likelihood-free methods in PyTorch.☆39Updated 4 years ago
- ☆111Updated 6 years ago
- Lightweight library of stochastic gradient MCMC algorithms written in JAX.☆96Updated last year
- ☆45Updated last year
- Combining smooth constraint for building DAG with normalizing flow in order to replace autoregressive transformations while keeping tract…☆44Updated last year
- Hamiltonian Dynamics with Non-Newtonian Momentum for Rapid Sampling☆36Updated 3 years ago
- Code for efficiently sampling functions from GP(flow) posteriors☆66Updated 4 years ago
- Simulation-based inference benchmark☆91Updated this week
- A Python package for efficient optimisation of real-space renormalization group transformations using Tensorflow.☆27Updated last month
- Support material for MAT6115, Université de Montréal, Fall 2018☆25Updated 10 months ago
- Implementation of approximate free-energy minimization in PyTorch☆18Updated 3 years ago
- Code used for experiments in https://arxiv.org/abs/2008.08601☆17Updated 3 years ago
- Conditional density estimation with neural networks☆27Updated 3 months ago
- Library for normalizing flows and neural flows.☆24Updated 2 years ago
- Riemannian Optimization Using JAX☆45Updated last year
- A generic interface for linear algebra backends☆70Updated 4 months ago
- Continuous-time gradient flow for generative modeling and variational inference☆29Updated 6 years ago
- Bayesian inference with Python and Jax.☆31Updated last year
- RKHS feature vectors, operators, and statistical models using JAX for automatic differentiation☆8Updated 3 years ago
- ☆14Updated 5 years ago
- A variational method for fast, approximate inference for stochastic differential equations.☆43Updated 6 years ago
- ☆20Updated 3 months ago
- Repository for Deterministic Particle Flow Control framework☆10Updated 2 years ago
- Code for "Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations"☆170Updated 2 years ago
- Normalizing Flows using JAX☆82Updated 11 months ago
- Code for 'Solving Statistical Mechanics using Variational Autoregressive Networks'.☆91Updated 3 months ago
- Code for Gaussian Score Matching Variational Inference☆28Updated last month
- Code repo for "Function-Space Distributions over Kernels"☆31Updated 3 years ago