lawrennd / old_talksLinks
Talks from Neil Lawrence
☆54Updated 2 years ago
Alternatives and similar repositories for old_talks
Users that are interested in old_talks are comparing it to the libraries listed below
Sorting:
- Exercises for the Tutorial on Approximate Bayesian Inference at the Data Science Summer School 2018☆22Updated 7 years ago
- Code repo for "Function-Space Distributions over Kernels"☆32Updated 4 years ago
- Library for Bayesian Neural Networks in PyTorch (first version as published in ProbProg2020)☆42Updated 4 years ago
- InferPy: Deep Probabilistic Modeling with Tensorflow Made Easy☆148Updated last year
- ☆50Updated last year
- ☆26Updated 7 years ago
- Variational Fourier Features☆86Updated 4 years ago
- Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)☆65Updated 6 years ago
- ☆30Updated 3 years ago
- Material for the practical of the DS3 course on "Representing and comparing probabilities with kernels"☆26Updated 6 years ago
- Sparse Orthogonal Variational Inference for Gaussian Processes (SOLVE-GP)☆22Updated 4 years ago
- Code repository for the generalized Galton board example in the paper "Mining gold from implicit models to improve likelihood-free infere…☆34Updated 6 years ago
- Non-stationary spectral mixture kernels implemented in GPflow☆28Updated 7 years ago
- Deep Gaussian Processes with Doubly Stochastic Variational Inference☆151Updated 6 years ago
- Repo to accompany paper "Implicit Self-Regularization in Deep Neural Networks..."☆47Updated 6 years ago
- Bayesian Optimisation over Multiple Continuous and Categorical Inputs (CoCaBO)☆52Updated 6 years ago
- PyData San Luis 2017 Tutorial: An Introduction to Gaussian Processes in PyMC3☆15Updated 8 years ago
- stand alone Neural Additive Models, forked from google-reasearch for easy import to colab☆29Updated 5 years ago
- A variational method for fast, approximate inference for stochastic differential equations.☆45Updated 7 years ago
- pyrff: Python implementation of random fourier feature approximations for gaussian processes☆28Updated 5 months ago
- OxCSML research group reading groups and meetings at the Department of Statistics, University of Oxford.☆95Updated 4 years ago
- Code for AutoGP☆27Updated 6 years ago
- Reducing Reparameterization Gradient Variance code.☆33Updated 8 years ago
- Re-Examining Linear Embeddings for High-dimensional Bayesian Optimization☆42Updated 4 years ago
- Gaussian Process and Uncertainty Quantification Summer School 2020☆33Updated 3 years ago
- TensorFlow implementation for training MCMC samplers from the paper: Generalizing Hamiltonian Monte Carlo with Neural Network☆183Updated 7 years ago
- ☆40Updated 6 years ago
- Variational inference for hierarchical dynamical systems☆48Updated last year
- my PhD thesis on Bayesian inference☆27Updated 12 years ago
- Exploring Bayesian Optimization☆76Updated 4 years ago