fbach2000 / Learning_Theory_from_First_Principles
Python & Matlab code for the figures from the book "Learning Theory from First Principles" by Francis Bach
☆99Updated last year
Alternatives and similar repositories for Learning_Theory_from_First_Principles:
Users that are interested in Learning_Theory_from_First_Principles are comparing it to the libraries listed below
- ☆137Updated last week
- Official Github for Wharton STAT 4830☆26Updated last week
- The optimal ridge penalty for real-world high-dimensional data can be zero or negative due to the implicit ridge regularization☆32Updated 3 years ago
- Matlab Notebook for visualizing random matrix theory results and their applications to machine learning☆117Updated last year
- Material for the "Probabilistic Machine Learning" Course at the University of Tübingen, Summer Term 2023☆147Updated last year
- About A collection of AWESOME things about information geometry Topics☆156Updated 9 months ago
- Notes for the Numerics of Machine Learning Lecture Course at the University of Tübingen☆198Updated last year
- Interactive textbook on state-space models☆184Updated last year
- Recursive Bayesian Estimation (Sequential / Online Inference)☆58Updated 11 months ago
- Material for the course Large-Scale Convex Optimisation at LTH, autumn 2020☆14Updated 4 years ago
- ☆28Updated 2 months ago
- Materials of the Nordic Probabilistic AI School 2023.☆89Updated last year
- ☆222Updated 2 years ago
- Loopy belief propagation for factor graphs on discrete variables in JAX☆144Updated 5 months ago
- Code for the book "The Elements of Differentiable Programming".☆77Updated 2 weeks ago
- A primer on Bayesian Neural Networks. The aim of this reading list is to facilitate the entry of new researchers into the field of Bayesi…☆52Updated last year
- Resources for education in statistics and machine learning: from advanced undergraduate to research level☆90Updated 10 months ago
- Scalable Convex Neural Networks☆23Updated last week
- Agustinus' very opiniated publication-ready plotting library☆62Updated 2 months ago
- Materials of the Nordic Probabilistic AI School 2022.☆175Updated 2 years ago
- Repository for my Big Data Optimization course☆34Updated 4 years ago
- Utilities for probabilistic ML☆33Updated last year
- 18.065/18.0651: Matrix Methods in Data Analysis, Signal Processing, and Machine Learning☆155Updated 5 months ago
- This repository contains a Jax implementation of conformal training corresponding to the ICLR'22 paper "learning optimal conformal classi…☆129Updated 2 years ago
- Neat Bayesian machine learning examples☆55Updated 2 months ago
- Course 5SSD0 - Bayesian Machine Learning and Information Processing☆42Updated last week
- 🌀 Stanford CS 228 - Probabilistic Graphical Models☆81Updated 6 years ago
- Materials and syllabus for Cornell ORIE 7391, Faster: Algorithmic Ideas for Speeding Up Optimization☆23Updated 2 years ago
- Riemannian Optimization Using JAX☆48Updated last year
- Parameter-Free Optimizers for Pytorch☆122Updated 11 months ago