introdeeplearning / book
Code for the book "Mathematical Introduction to Deep Learning: Methods, Implementations, and Theory"
☆119Updated last year
Related projects ⓘ
Alternatives and complementary repositories for book
- NYU Artificial Intelligence Spring 2024☆49Updated 3 weeks ago
- Material for the "Probabilistic Machine Learning" Course at the University of Tübingen, Summer Term 2023☆131Updated last year
- ☆70Updated last year
- Modern Graph Theory Algorithms with Python, published by Packt☆22Updated 5 months ago
- This repository contains a better implementation of Kolmogorov-Arnold networks☆59Updated 6 months ago
- Collection of tests performed during the study of the new Kolmogorov-Arnold Neural Networks (KAN)☆34Updated last month
- Here are the notebooks for the Gaussian Processes and Bayesian Optimization course. The notebooks can be executed in Google Colab.☆26Updated 4 months ago
- Resources for education in statistics and machine learning: from advanced undergraduate to research level☆83Updated 6 months ago
- Material for the hands-on tutorial on Graph Deep Learning held at the Alan Turing Institute☆56Updated 11 months ago
- Interactive textbook on state-space models☆176Updated 9 months ago
- Notes for the Numerics of Machine Learning Lecture Course at the University of Tübingen☆189Updated 7 months ago
- A course on Linear Algebra using Python in Jupyter notebooks☆25Updated last year
- Understanding Kolmogorov-Arnold Networks: A Tutorial Series on KAN using Toy Examples☆166Updated last month
- Neat Bayesian machine learning examples☆54Updated last month
- ☆25Updated 3 months ago
- Python code (in the form of Jupyter ipython notebooks) to support the book "Math and Architectures of Deep Learning" (Krishnendu Chaudhur…☆144Updated 5 months ago
- Python & Matlab code for the figures from the book "Learning Theory from First Principles" by Francis Bach☆36Updated 8 months ago
- The code for "Diffusion Geometry" (2024).☆33Updated 5 months ago
- Automatic Integration for Neural Spatio-Temporal Point Process models (AI-STPP) is a new paradigm for exact, efficient, non-parametric inf…☆24Updated last month
- Enhancing Deep Learning with Bayesian Inference, published by Packt☆31Updated last month
- Debugging Machine Learning Models with Python, published by Packt☆50Updated last year
- Notebooks for the "JAX in Action" book☆116Updated 5 months ago
- Kolmogorov–Arnold Networks with modified activation (using MLP to represent the activation)☆103Updated 3 weeks ago
- ☆39Updated 2 years ago
- This code implements a Radial Basis Function (RBF) based Kolmogorov-Arnold Network (KAN) for function approximation.☆25Updated 5 months ago
- ☆100Updated this week
- Code for the AISTATS 2024 Paper "From Data Imputation to Data Cleaning - Automated Cleaning of Tabular Data Improves Downstream Predictiv…☆19Updated 9 months ago
- Cross-prediction-powered inference☆13Updated 6 months ago
- Notes, exercises and other materials related to causal inference, causal discovery and causal ML.☆128Updated 3 months ago
- A short introduction to Conformal Prediction methods, with a few examples for classification and regression from the Astrophysical domain…☆12Updated 4 months ago