19 Repositories
Python fractal-dimension Libraries
In this repo we reproduce and extend results of Learning in High Dimension Always Amounts to Extrapolation by Balestriero et al. 2021
In this repo we reproduce and extend results of Learning in High Dimension Always Amounts to Extrapolation by Balestriero et al. 2021. Balestriero et
Dimension Reduced Turbulent Flow Data From Deep Vector Quantizers
Dimension Reduced Turbulent Flow Data From Deep Vector Quantizers This is an implementation of A Physics-Informed Vector Quantized Autoencoder for Dat
Repository for the AugmentedPCA Python package.
Overview This Python package provides implementations of Augmented Principal Component Analysis (AugmentedPCA) - a family of linear factor models that
An executor that wraps 3D mesh models and encodes 3D content documents to d-dimension vector.
3D Mesh Encoder An Executor that receives Documents containing point sets data in its blob attribute, with shape (N, 3) and encodes it to embeddings o
DUQ is a python package for working with physical Dimensions, Units, and Quantities.
DUQ is a python package for working with physical Dimensions, Units, and Quantities.
Neural-fractal - Create Fractals Using Complex-Valued Neural Networks!
Neural Fractal Create Fractals Using Complex-Valued Neural Networks! Home Page Features Define Dynamical Systems Using Complex-Valued Neural Networks
A Python library for working with arbitrary-dimension hypercomplex numbers following the Cayley-Dickson construction of algebras.
Hypercomplex A Python library for working with quaternions, octonions, sedenions, and beyond following the Cayley-Dickson construction of hypercomplex
A small script written in Python3 that generates a visual representation of the Mandelbrot set.
Mandelbrot Set Generator A small script written in Python3 that generates a visual representation of the Mandelbrot set. Abstract The colors in the ou
Official implementation of "Intrinsic Dimension, Persistent Homology and Generalization in Neural Networks", NeurIPS 2021.
PHDimGeneralization Official implementation of "Intrinsic Dimension, Persistent Homology and Generalization in Neural Networks", NeurIPS 2021. Overvie
Exploring dimension-reduced embeddings
sleepwalk Exploring dimension-reduced embeddings This is the code repository. See here for the Sleepwalk web page. License and disclaimer This program
A Python 3 package for state-of-the-art statistical dimension reduction methods
direpack: a Python 3 library for state-of-the-art statistical dimension reduction techniques This package delivers a scikit-learn compatible Python 3
A simple python script that print the Mandelbrot set for every power of the formal formula.
Python Mandelbrot A simple python script that print the Mandelbrot set for every power of the formal formula.
Collection of scripts for making high quality beautiful math-related posters.
Poster Collection of scripts for making high quality beautiful math-related posters. The poster can have as large printing size as 3x2 square feet wit
Source code release of the paper: Knowledge-Guided Deep Fractal Neural Networks for Human Pose Estimation.
GNet-pose Project Page: http://guanghan.info/projects/guided-fractal/ UPDATE 9/27/2018: Prototxts and model that achieved 93.9Pck on LSP dataset. http
Python implementation of Newton's Fractal
Newton's Fractal Animates Newton's fractal between two polynomials of the same order. Inspired by this video by 3Blue1Brown. Example fractals can be f
Code for "The Intrinsic Dimension of Images and Its Impact on Learning" - ICLR 2021 Spotlight
dimensions Estimating the instrinsic dimensionality of image datasets Code for: The Intrinsic Dimensionaity of Images and Its Impact On Learning - Phi
Implementation of "Bidirectional Projection Network for Cross Dimension Scene Understanding" CVPR 2021 (Oral)
Bidirectional Projection Network for Cross Dimension Scene Understanding CVPR 2021 (Oral) [ Project Webpage ] [ arXiv ] [ Video ] Existing segmentatio
AntroPy: entropy and complexity of (EEG) time-series in Python
AntroPy is a Python 3 package providing several time-efficient algorithms for computing the complexity of time-series. It can be used for example to e
A fast xgboost feature selection algorithm
BoostARoota A Fast XGBoost Feature Selection Algorithm (plus other sklearn tree-based classifiers) Why Create Another Algorithm? Automated processes l