jessstringham / notebooks
Jupyter notebooks for my blog
☆31Updated 5 years ago
Alternatives and similar repositories for notebooks:
Users that are interested in notebooks are comparing it to the libraries listed below
- Python 3.7 version of David Barber's MATLAB BRMLtoolbox☆24Updated 6 years ago
- Materials for class on topics in deep learning (STAT 991, UPenn/Wharton)☆94Updated 2 years ago
- Probabilistic graphical models in python☆22Updated 5 years ago
- Code used in the causality course (401-4632-15) at ETH Zurich.☆21Updated 5 years ago
- Materials for ORIE 7191: Topics in Optimization for Machine Learning☆43Updated 5 years ago
- Dropout as Regularization and Bayesian Approximation☆57Updated 6 years ago
- Variational Inference in Gaussian Mixture Model☆58Updated 4 years ago
- Know Your Boundaries: Constraining Gaussian Processes by Variational Harmonic Features☆23Updated 5 years ago
- A didactic Python library with well-commented and annotated implementations of machine learning algorithms.☆51Updated 4 years ago
- Gaussian Process and Uncertainty Quantification Summer School 2020☆33Updated 2 years ago
- Course material for the PhD course in Advanced Bayesian Learning☆59Updated 3 months ago
- Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)☆64Updated 5 years ago
- Gaussian process regression + automatical model selection for logitudinal -omics data☆21Updated 3 years ago
- Collected code and materials from the intensive course preparing for the workshop on Sequential Monte Carlo (SMC) methods at Uppsala Univ…☆21Updated 6 years ago
- Source code and data for the tutorial: "Getting started with particle Metropolis-Hastings for inference in nonlinear models"☆28Updated 5 years ago
- Hierarchical Change-Point Detection☆14Updated 6 years ago
- Implementation of the Gaussian processes regression with inducing points for online data with ensemble Kalman filter estimation. Code for…☆17Updated 6 years ago
- I am in [research] stepped in so far that, should I wade no more, Returning were as tedious as go o'er. -MacBeth☆181Updated 10 years ago
- Python implementation of the PR-SSM.☆51Updated 6 years ago
- ☆28Updated 6 years ago
- Deep Gaussian Processes with Doubly Stochastic Variational Inference☆148Updated 5 years ago
- Talks from Neil Lawrence☆54Updated last year
- Code for Randomly Projected Additive Gaussian Processes☆25Updated 5 years ago
- The code in this repository follows the paper "Stochastic gradient MCMC"☆25Updated 5 years ago
- machine learning☆37Updated 6 years ago
- Materials of the Nordic Probabilistic AI School 2019.☆129Updated 4 years ago
- Unbiased Markov chain Monte Carlo with couplings☆29Updated 2 years ago
- A distributed version of the sparse multi-output Gaussian process framework integrating python and C++.☆29Updated 6 years ago
- Example codes for the book Applied Stochastic Differential Equations☆182Updated 3 years ago
- Dirichlet Process K-means☆47Updated 8 months ago