f-dangel / phd-thesisLinks
Source code for my PhD thesis: Backpropagation Beyond the Gradient
☆20Updated 2 years ago
Alternatives and similar repositories for phd-thesis
Users that are interested in phd-thesis are comparing it to the libraries listed below
Sorting:
- Tutorial materials of the Probabilistic Numerics Spring School.☆35Updated 2 years ago
- Sketched linear operations for PyTorch☆100Updated 2 months ago
- Code for "Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations"☆171Updated 3 years ago
- Kernel Stein Discrepancy Descent : a method to sample from unnormalized densities☆22Updated last year
- Normalizing Flows using JAX☆85Updated 2 years ago
- A generic interface for linear algebra backends☆75Updated last month
- [TMLR 2022] Curvature access through the generalized Gauss-Newton's low-rank structure: Eigenvalues, eigenvectors, directional derivative…☆17Updated 2 years ago
- Code for efficiently sampling functions from GP(flow) posteriors☆74Updated 5 years ago
- An ultra-lightweight JAX implementation of sparse Gaussian processes via pathwise sampling.☆22Updated 4 years ago
- Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)☆20Updated 6 years ago
- Bayes-Newton—A Gaussian process library in JAX, with a unifying view of approximate Bayesian inference as variants of Newton's method.☆241Updated 2 years ago
- A framework for composing Neural Processes in Julia☆76Updated 4 years ago
- Approximate inference for Markov Gaussian processes using iterated Kalman smoothing, in JAX☆102Updated 2 years ago
- An implementation of squared neural families in PyTorch☆14Updated last year
- Gaussian Processes for Sequential Data☆19Updated 5 years ago
- Robust initialisation of inducing points in sparse variational GP regression models.☆34Updated 3 years ago
- Riemannian Convex Potential Maps☆67Updated 2 years ago
- Lightweight library of stochastic gradient MCMC algorithms written in JAX.☆105Updated 2 years ago
- PyTorch linear operators for curvature matrices (Hessian, Fisher/GGN, KFAC, ...)☆61Updated last week
- IVON optimizer for neural networks based on variational learning.☆80Updated last year
- Probabilistic solvers for differential equations in JAX. Adaptive ODE solvers with calibration, state-space model factorisations, and cus…☆53Updated last month
- Algorithms for computations on random manifolds made easier☆94Updated 2 years ago
- A Julia implementation of sparse Gaussian processes via path-wise doubly stochastic variational inference.☆33Updated 5 years ago
- Large-scale, multi-GPU capable, kernel solver☆196Updated 5 months ago
- Efficient SDE samplers including Gaussian-based probabilistic solvers. Written in JAX.☆10Updated 10 months ago
- Recursive Bayesian Estimation (Sequential / Online Inference)☆60Updated last year
- Pulls papers from arXiv on a weekly basis☆30Updated 2 years ago
- Lightweight MCMC sampling for PyTorch Models aka My Corona Project☆52Updated 4 months ago
- Normalizing Flows with a resampled base distribution☆47Updated 3 years ago
- Matrix-free linear algebra in JAX.☆153Updated last month