codebase for "A Theory of the Inductive Bias and Generalization of Kernel Regression and Wide Neural Networks"
☆51May 2, 2023Updated 2 years ago
Alternatives and similar repositories for eigenlearning
Users that are interested in eigenlearning are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- Code accompanying our paper "Finding trainable sparse networks through Neural Tangent Transfer" to be published at ICML-2020.☆13Jun 14, 2020Updated 5 years ago
- Pytorch based implementation of Upside Down Reinforcement Learning (UDRL) by J. Schmidhuber et al.☆12May 1, 2020Updated 5 years ago
- Fast and Easy Infinite Neural Networks in Python☆2,381Mar 1, 2024Updated 2 years ago
- Single shot neural network pruning before training the model, based on connection sensitivity☆11Aug 7, 2019Updated 6 years ago
- ☆11Oct 14, 2019Updated 6 years ago
- Deploy on Railway without the complexity - Free Credits Offer • AdConnect your repo and Railway handles the rest with instant previews. Quickly provision container image services, databases, and storage volumes.
- Daily Neural Network Practice Season 3! ( Finishing up Masters)☆10Sep 9, 2019Updated 6 years ago
- Implementation of unregularized, l1 regularized and l2 regularized linear regression using numpy and without sklearn☆12Oct 4, 2019Updated 6 years ago
- A toolkit to induce interpretable workflows from raw computer-use activities.☆42Nov 13, 2025Updated 5 months ago
- Geometric Certifications of Neural Nets☆42Nov 22, 2022Updated 3 years ago
- Material for the Advanced Scientific Programming in Python course on data visualization☆17Sep 3, 2018Updated 7 years ago
- Experiment Manager☆22Jan 15, 2020Updated 6 years ago
- Array quantization and compression☆14Dec 8, 2023Updated 2 years ago
- DON'T PANIC (a not so useful guide to High Energy Physics software)☆13Feb 23, 2022Updated 4 years ago
- ☆12Mar 25, 2023Updated 3 years ago
- End-to-end encrypted cloud storage - Proton Drive • AdSpecial offer: 40% Off Yearly / 80% Off First Month. Protect your most important files, photos, and documents from prying eyes.
- These are tutorials on how to use Pandas Data Frames for professional astronomy. Import common types of astronomical data, filter, sort,…☆12Sep 27, 2018Updated 7 years ago
- This is a course material for numerical optimization to be taught in summer 2020☆41Jul 15, 2020Updated 5 years ago
- Prangster tool from the Black Hat USA 2013 presentation "Black-Box Assessment of Pseudorandom Algorithms" by Derek Soeder, Christopher Ab…☆11Jul 9, 2014Updated 11 years ago
- ☆68Mar 15, 2019Updated 7 years ago
- Pretrained TorchVision models on CIFAR10 dataset (with weights)☆23Aug 17, 2020Updated 5 years ago
- Official Code of The Combinatorial Brain Surgeon: Pruning Weights That Cancel One Another in Neural Networks[ICML2022]☆16Sep 20, 2022Updated 3 years ago
- Galaxy Docker Image for the HiCExplorer☆11Mar 3, 2019Updated 7 years ago
- Code for testing DCT plus Sparse (DCTpS) networks☆14Jun 15, 2021Updated 4 years ago
- ☆11Jun 7, 2023Updated 2 years ago
- Serverless GPU API endpoints on Runpod - Get Bonus Credits • AdSkip the infrastructure headaches. Auto-scaling, pay-as-you-go, no-ops approach lets you focus on innovating your application.
- ☆11Apr 17, 2021Updated 5 years ago
- ☆13Dec 28, 2023Updated 2 years ago
- Code for the paper: "Tensor Programs II: Neural Tangent Kernel for Any Architecture"☆109Aug 26, 2020Updated 5 years ago
- ☆10Jan 19, 2026Updated 3 months ago
- Ada-LISTA: Learned Solvers Adaptive to Varying Models☆11Feb 18, 2020Updated 6 years ago
- FFT Explorations (basic implementation)☆10Aug 8, 2014Updated 11 years ago
- Making a bridge between NLP models and Brain data☆19Jun 3, 2020Updated 5 years ago
- Machine Learning: a New Toolbox for Theoretical Physics (Advanced Topics in Theoretical Physics course)☆13Dec 9, 2019Updated 6 years ago
- Code for random Fourier features based on Rahimi and Recht's 2007 paper.☆59Dec 21, 2020Updated 5 years ago
- Serverless GPU API endpoints on Runpod - Get Bonus Credits • AdSkip the infrastructure headaches. Auto-scaling, pay-as-you-go, no-ops approach lets you focus on innovating your application.
- Error-free transformations are used to get results with extra accuracy.☆15Jan 20, 2025Updated last year
- Codebase for Learning Invariances in Neural Networks☆96Oct 7, 2022Updated 3 years ago
- Sparse representation solvers for P0- and P1-problems☆10Nov 30, 2023Updated 2 years ago
- A library for managing undo and redo commands☆16Nov 7, 2024Updated last year
- R package for weighted model metrics☆11Apr 12, 2025Updated last year
- A simple implementation of a deep linear Pytorch module☆21Oct 16, 2020Updated 5 years ago
- ☆12Jul 22, 2022Updated 3 years ago