RussellTsuchida / snefyLinks
An implementation of squared neural families in PyTorch
☆14Updated 9 months ago
Alternatives and similar repositories for snefy
Users that are interested in snefy are comparing it to the libraries listed below
Sorting:
- Source code for my PhD thesis: Backpropagation Beyond the Gradient☆20Updated 2 years ago
- An ultra-lightweight JAX implementation of sparse Gaussian processes via pathwise sampling.☆22Updated 4 years ago
- Sketched matrix decompositions for PyTorch☆70Updated this week
- ☆52Updated 2 years ago
- A generic interface for linear algebra backends☆73Updated 4 months ago
- Agustinus' very opiniated publication-ready plotting library☆67Updated 2 months ago
- Tutorial materials of the Probabilistic Numerics Spring School.☆34Updated 2 years ago
- Public code for running Stochastic Gradient Descent on GPs.☆39Updated 3 months ago
- Code for 'Periodic Activation Functions Induce Stationarity' (NeurIPS 2021)☆19Updated 3 years ago
- Riemannian Convex Potential Maps☆67Updated 2 years ago
- Matrix-free linear algebra in JAX.☆129Updated this week
- Lightweight MCMC sampling for PyTorch Models aka My Corona Project☆48Updated this week
- Normalizing Flows using JAX☆83Updated last year
- Kernel Stein Discrepancy Descent : a method to sample from unnormalized densities☆21Updated last year
- Bayesian inference with Python and Jax.☆33Updated 2 years ago
- Supplementary code for the paper "Stationary Kernels and Gaussian Processes on Lie Groups and their Homogeneous Spaces"☆43Updated last year
- Probabilistic solvers for differential equations in JAX. Adaptive ODE solvers with calibration, state-space model factorisations, and cus…☆49Updated 3 months ago
- Source code for Large-Scale Wasserstein Gradient Flows (NeurIPS 2021)☆33Updated 3 years ago
- Efficient SDE samplers including Gaussian-based probabilistic solvers. Written in JAX.☆10Updated 5 months ago
- Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)☆20Updated 6 years ago
- Riemannian Optimization Using JAX☆50Updated last year
- Squared Non-monotonic Probabilistic Circuits☆22Updated 6 months ago
- Library for normalizing flows and neural flows.☆25Updated 3 years ago
- Conditional Flow Matching using JAX☆13Updated 2 years ago
- Code for "Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations"☆171Updated 3 years ago
- Hamiltonian Dynamics with Non-Newtonian Momentum for Rapid Sampling☆36Updated 3 years ago
- [TMLR 2022] Curvature access through the generalized Gauss-Newton's low-rank structure: Eigenvalues, eigenvectors, directional derivative…☆17Updated 2 years ago
- Free-form flows are a generative model training a pair of neural networks via maximum likelihood☆45Updated last month
- A framework for composing Neural Processes in Julia☆76Updated 4 years ago
- Code for "'Hey, that's not an ODE:' Faster ODE Adjoints via Seminorms" (ICML 2021)☆87Updated 2 years ago