Zhenyu-LIAO / RMT4ML
Matlab Notebook for visualizing random matrix theory results and their applications to machine learning
☆113Updated last year
Alternatives and similar repositories for RMT4ML:
Users that are interested in RMT4ML are comparing it to the libraries listed below
- some important properties on random matrix theory and its applications in multiple areas☆106Updated 6 years ago
- Summer course on mathematical theory of deep learning☆52Updated 5 years ago
- Sampling with gradient-based Markov Chain Monte Carlo approaches☆93Updated 8 months ago
- ☆214Updated 2 years ago
- ☆110Updated 7 years ago
- A feasible method for optimization with orthogonality constraints☆39Updated 3 years ago
- Welcome to the Awesome Feature Learning in Deep Learning Thoery Reading Group! This repository serves as a collaborative platform for sch…☆157Updated 3 weeks ago
- The code in this repository follows the paper "Stochastic gradient MCMC"☆25Updated 5 years ago
- Code for ICE-BeeM paper - NeurIPS 2020☆86Updated 3 years ago
- Advanced LTCC course in StatisticsThis course will provide an overview of Monte Carlo methods when used for problems in Statistics. After…☆24Updated 2 years ago
- Materials and syllabus for Cornell ORIE 7391, Faster: Algorithmic Ideas for Speeding Up Optimization☆22Updated 2 years ago
- Mutual information estimators and benchmark☆39Updated last month
- ☆23Updated 3 years ago
- Code for random Fourier features based on Rahimi and Recht's 2007 paper.☆52Updated 4 years ago
- ☆67Updated 5 years ago
- Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)☆20Updated 5 years ago
- LaTeX style file for the Journal of Machine Learning Research☆120Updated 6 months ago
- Random Matrix Theory library - RMT analysis and simulation in Python☆46Updated 9 months ago
- My notes from class☆61Updated 6 years ago
- Pulls papers from arXiv on a weekly basis☆30Updated last year
- Example codes for the book Applied Stochastic Differential Equations☆182Updated 3 years ago
- Neural Tangent Kernel Papers☆101Updated this week
- Code for "Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations"☆169Updated 2 years ago
- This repo contains papers, books, tutorials and resources on Riemannian optimization.☆28Updated last month
- Codes for ICLR 21 paper: Neural Approximate Sufficient Statistics for Implicit Models☆19Updated 2 years ago
- Learn then Test: Calibrating Predictive Algorithms to Achieve Risk Control☆65Updated 2 months ago
- Python & Matlab code for the figures from the book "Learning Theory from First Principles" by Francis Bach☆74Updated 10 months ago
- Adaptive gradient descent without descent☆47Updated 3 years ago
- Deep universal probabilistic programming with Python and PyTorch☆11Updated 4 years ago
- Code for the paper "Bayesian Neural Network Priors Revisited"☆55Updated 3 years ago