fbach2000 / Learning_Theory_from_First_PrinciplesLinks
Python & Matlab code for the figures from the book "Learning Theory from First Principles" by Francis Bach
☆114Updated 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
Sorting:
- Matlab Notebook for visualizing random matrix theory results and their applications to machine learning☆123Updated 2 years ago
- Code for the book "Mathematical Introduction to Deep Learning: Methods, Implementations, and Theory"☆152Updated last year
- ☆140Updated last month
- About A collection of AWESOME things about information geometry Topics☆164Updated last year
- Notes for the Numerics of Machine Learning Lecture Course at the University of Tübingen☆210Updated last year
- Material for the "Probabilistic Machine Learning" Course at the University of Tübingen, Summer Term 2023☆167Updated last year
- Solution Manual for Roman Vershynin's High-Dimensional Probability☆23Updated 11 months ago
- Code for the book "The Elements of Differentiable Programming".☆241Updated 3 weeks ago
- Deep Learning, an Energy Approach☆187Updated last month
- Interactive textbook on state-space models☆194Updated last year
- Official Github for Wharton STAT 4830☆40Updated last month
- MIT IAP short course: Matrix Calculus for Machine Learning and Beyond☆512Updated 5 months ago
- 18.065/18.0651: Matrix Methods in Data Analysis, Signal Processing, and Machine Learning☆170Updated 8 months ago
- ☆29Updated 5 months ago
- Patched Attention for Nonlinear Dynamics☆150Updated 2 weeks ago
- Neat Bayesian machine learning examples☆58Updated 2 weeks ago
- The optimal ridge penalty for real-world high-dimensional data can be zero or negative due to the implicit ridge regularization☆31Updated 3 years ago
- Recursive Bayesian Estimation (Sequential / Online Inference)☆59Updated last year
- ☆81Updated 2 years ago
- Machine Learning with Symbolic Tensors☆316Updated last month
- Repository for my Big Data Optimization course☆34Updated 4 years ago
- Loopy belief propagation for factor graphs on discrete variables in JAX☆154Updated 8 months ago
- Harvard Applied Math 205: Code Examples☆88Updated 2 years ago
- Material for the course Large-Scale Convex Optimisation at LTH, autumn 2020☆14Updated 4 years ago
- Parameter-Free Optimizers for Pytorch☆130Updated last year
- Course 5SSD0 - Bayesian Machine Learning and Information Processing☆48Updated 3 months ago
- Materials of the Nordic Probabilistic AI School 2022.☆181Updated 2 years ago
- Utilities for probabilistic ML☆36Updated last year
- ☆50Updated last year
- Introduction to Gaussian Processes☆29Updated 7 years ago