Python Rf-double-descent Resources

30-Days-of-ML-Kaggle 🔥 About the Hands On Program 💻 Machine learning beginner → Kaggle competitor in 30 days. Non-coders welcome The program starts

The Implicit Bias of Gradient Descent on Generalized Gated Linear Networks This folder contains the code to reproduce the data in "The Implicit Bias o

Nonlinear Optimization Algorithms During my time as Scientific Assistant at the Karlsruhe Institute of Technology (Germany) I implemented various Opti

Phase diagram of Stochastic Gradient Descent in high-dimensional two-layer neural networks Under construction. Description Code for Phase diagram of S

split-manga-pages split-manga-pages is a command line utility written in Python that converts your double-page layout manga (or any images in double p

An implementation of the Fibonacci method for gradient descent, featuring a TKinter GUI for inputting the function / parameters to be examined and a matplotlib plot of the function and results.

FedDCD.jl Implementation of the federated dual coordinate descent (FedDCD) method. Installation To install, just call Pkg.add("https://github.com/Zhen

Born-Infeld (BI) for AI: Energy-Conserving Descent (ECD) for Optimization This repository contains the code for the BBI optimizer, introduced in the p

Neuron class provides LNU (Linear Neural Unit), QNU (Quadratic Neural Unit), RBF (Radial Basis Function), MLP (Multi Layer Perceptron), MLP-ELM (Multi Layer Perceptron - Extreme Learning Machine) neurons learned with Gradient descent or LeLevenberg–Marquardt algorithm

This is a python project which detects color of an image when you double click on it. You have to press ESC button to close the pop-up Image window. There are mainly two library CV2 and Pandas that are used in this project.

CVE-2022-21907 - Double Free in http.sys driver Summary An unauthenticated attacker can send an HTTP request with an "Accept-Encoding" HTTP request he

Symplectic Double Pendulum Simulator Double pendulum simulator using a symplectic Euler's method. The program calculates the momentum and position of

Plotting intersection of curves using gradient descent Webapp Link --- What's the app about Why this app Plotting functions and their intersection. A

shaplets Python implementation of the Learning Time-Series Shapelets method by Josif Grabocka et al., that learns a shapelet-based time-series classif

ieee754 ieee754 is small Python library which gives you the IEEE-754 representation of a floating point number. You can specify a precision given in t

beancount: Double-Entry Accounting from Text Files Contents Description Documentation Download & Installation Versions Filing Bugs Copyright and Licen

Distributed Grid Descent: an algorithm for hyperparameter tuning guided by Bayesian inference, designed to run on multiple processes and potentially many machines with no central point of control.

Tianshou (天授) is a reinforcement learning platform based on pure PyTorch. Unlike existing reinforcement learning libraries, which are mainly based on

Minimisation of a negative log likelihood fit to extract the lifetime of the D^0 meson (MNLL2ELDM) Introduction The average lifetime of the $D^{0}$ me

MDM A Tensorflow implementation of the Mnemonic Descent Method. Mnemonic Descent Method: A recurrent process applied for end-to-end face alignment G.

Grow Function: A 3D Stacked Bifurcating Double Deep Cellular Automata which differentiates using a Genetic Algorithm... TLDR;High Def Trees that you can mint as NFTs on Solana

Online Learning Of Neural Computations From Sparse Temporal Feedback This repository is the official implementation of the NeurIPS 2021 paper Online L

Double Cube Engravings This script creates a dataset for multi-label mesh clasification, with an intentionally difficult setup for point cloud classif

PyNNDescent PyNNDescent is a Python nearest neighbor descent for approximate nearest neighbors. It provides a python implementation of Nearest Neighbo

InfiniteBoost Code for a paper InfiniteBoost: building infinite ensembles with gradient descent (arXiv:1706.01109). A. Rogozhnikov, T. Likhomanenko De

kwd-extraction-study This repository is maintained for the scientific paper tittled " Study of keyword extraction techniques for Electric Double Layer

Stochastic Model Building (SMB) This repository includes a new fast and robust stochastic optimization algorithm for training deep learning models. Th

Welcome to PDF-double-side! Hi! I'm 15. I have a old printer so I can't print double-sided outs. The goal of this project is for anyone with an old pr

DQN/DDQN-Pytorch This is a clean and robust Pytorch implementation of DQN and Double DQN. Here is the training curve: All the experiments are trained

Code for the paper "There is no Double-Descent in Random Forests" This repository contains the code to run the experiments for our paper called "There

SGD-Linear-Regressor Iterative stochastic gradient descent (SGD) linear regressor with regularization Dataset: Kaggle “Graduate Admission 2” https://w

This bug doesn’t exist on x86: Exploiting an ARM-only race condition How to exploit a double free and get a shell. "Use-After-Free for dummies" In thi

Control Raspberry pi with physically attached button. Wake, Power Off, and Restart (Double Press) . Python3 script runs as a service with easy installation.

Stochastic Training is Not Necessary for Generalization -- Training competitive vision models without stochasticity This repository implements trainin

Intro PyTorch implementation of Learning to learn by gradient descent by gradient descent. Run python main.py TODO Initial implementation Toy data LST

Intro PyTorch implementation of Learning to learn by gradient descent by gradient descent. Run python main.py TODO Initial implementation Toy data LST

Show off your terminal, in style. A nice relaxing double pendulum simulation using ASCII, able to simulate multiple pendulums at once, and provide tra

Double Pendulum Using Curses in Python. A nice relaxing double pendulum simulation using ASCII, able to simulate multiple pendulums at once, and provi

REDQ source code Author's PyTorch implementation of Randomized Ensembled Double Q-Learning (REDQ) algorithm. Paper link: https://arxiv.org/abs/2101.05

Writing recursive-descent parsers by hand can be quite elegant but it's often a bit more verbose than expected, especially when it comes to handling indentation and reporting proper syntax errors. This package provides a powerful general-purpose token stream that addresses these issues and more.

Toy implementations of some popular ML optimizers using Python/JAX

Paddle-RLBooks Welcome to Paddle-RLBooks which is a reinforcement learning code study guide based on pure PaddlePaddle. 欢迎来到Paddle-RLBooks，该仓库主要是针对强化学

Neural Tangents ICLR 2020 Video | Paper | Quickstart | Install guide | Reference docs | Release notes Overview Neural Tangents is a high-level neural

Differentiable Morphing Image morphing without reference points by applying warp maps and optimizing over them. Differentiable Morphing is machine lea