bayesiains / reading-groupLinks
☆18Updated 5 years ago
Alternatives and similar repositories for reading-group
Users that are interested in reading-group are comparing it to the libraries listed below
Sorting:
- Normalizing Flows in Jax☆107Updated 4 years ago
- Monotone operator equilibrium networks☆53Updated 5 years ago
- Graduate topics course on learning discrete latent structure.☆67Updated 6 years ago
- ☆26Updated 6 years ago
- Autoregressive Energy Machines☆78Updated 2 years ago
- PyTorch implementation of Continuously Indexed Flows paper, with many baseline normalising flows☆31Updated 3 years ago
- ☆37Updated 6 years ago
- Pytorch implementation of Block Neural Autoregressive Flow☆181Updated 3 years ago
- Understanding normalizing flows☆132Updated 5 years ago
- Code for Unbiased Implicit Variational Inference (UIVI)☆14Updated 6 years ago
- Experiments for the Neural Autoregressive Flows paper☆125Updated 4 years ago
- ☆42Updated 6 years ago
- Code for the Thermodynamic Variational Objective☆26Updated 3 years ago
- BIVA: A Very Deep Hierarchy of Latent Variables forGenerative Modeling☆29Updated 5 years ago
- A public repository for our paper, Rao-Blackwellized Stochastic Gradients for Discrete Distributions☆22Updated 6 years ago
- Very deep VAEs in JAX/Flax☆46Updated 4 years ago
- ☆180Updated 6 years ago
- Optimization with orthogonal constraints and on general manifolds☆129Updated 5 years ago
- Pytorch implementation of the Power Spherical distribution☆74Updated last year
- Experiment code for "Randomized Automatic Differentiation"☆67Updated 5 years ago
- ☆22Updated 5 years ago
- A Python implementation of the gradient REBAR estimator.☆46Updated 7 years ago
- TensorFlow implementation of "noisy K-FAC" and "noisy EK-FAC".☆60Updated 6 years ago
- Computing the eigenvalues of Neural Tangent Kernel and Conjugate Kernel (aka NNGP kernel) over the boolean cube☆47Updated 5 years ago
- Riemannian Convex Potential Maps☆67Updated 2 years ago
- Neural likelihood-free methods in PyTorch.☆39Updated 5 years ago
- Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326☆71Updated 7 years ago
- Code accompanying VarGrad: A Low-Variance Gradient Estimator for Variational Inference☆12Updated 4 years ago
- ☆54Updated last year
- simple implementation of "Improved Variational Inference with Inverse Autoregressive Flow" paper with pytorch☆52Updated 7 years ago