Python Stroke-parameters Resources

Semi-automated OpenVINO benchmark_app with variable parameters. User can specify multiple options for any parameters in the benchmark_app and the progam runs the benchmark with all combinations of given options.

sam4onnx A very simple tool to rewrite parameters such as attributes and constants for OPs in ONNX models. Simple Attribute and Constant Modifier for

English: README-EN.md VRCWatch VRCWatch は、VRChat 内のアバター向けに現在時刻を送信するためのプログラムです。 使

frbmclust Getting Started Clusterize FRB profiles using hierarchical clustering,

Torch Mutable Modules Use in-place and assignment operations on PyTorch module p

A Python command-line utility for validating that the outputs of a given Declarative Form Azure Portal UI JSON template map to the input parameters of a given ARM Deployment Template JSON template

A-log-likelihood-fit-for-extracting-neutrino-oscillation-parameters Minimised the negative log-likelihood fit to extract neutrino oscillation paramete

implementation of MM1 and MMC Queue on randomly generated data and evaluate simulation results then compare with analytical results and draw a plot curve for them, simulate some integrals and compare results and run monte carlo algorithm with them

Optimizing synthesizer parameters using gradient approximation NASH 2021 Hackathon! These are some experiments I conducted during NASH 2021, the Neura

Evolving Neural Networks in JAX This repository holds code displaying techniques for applying evolutionary network training strategies in JAX. Each sc

A Python application that helps users determine their calorie intake, and automatically generates customized weekly meal and workout plans based on metrics computed using their physical parameters

Emport Overview This repo provides a FDTD (Finite Differences Time Domain) simulator called emport for solving RF circuits. Emport outputs its simulat

Advisor Introduction Advisor is the hyper parameters tuning system for black box optimization. It is the open-source implementation of Google Vizier w

stroke-predictions-ml-model machine learning model to predict individuals chance

have ansible installed locally run ansible-playbook setup_application.yml this sets up directories, installs system packages, and sets up python envir

Hyperparameter Optimization of Machine Learning Algorithms This code provides a hyper-parameter optimization implementation for machine learning algor

Simple program to easily view Euler parameters in 3D.

OctaDist Octahedral distortion calculator: A tool for calculating distortion parameters in coordination complexes. https://octadist.github.io/ Registe

Pricefy Car Price Predictor App used to predict the price of the car based on certain input parameters created using python's scikit-learn, fastapi, n

Pal Buddy Guy: The anipal's best friend This is a small script to improve upon the tracking capabilities of the Vive Pro Eye and facial tracker. You c

TikTok-Algorithm I found this python file from a source which was later deleted. Although the test api functions no longer seem to work, surprisingly

ShuttleNet: Position-aware Rally Progress and Player Styles Fusion for Stroke Forecasting in Badminton (AAAI 2022) Official code of the paper ShuttleN

ShuttleNet: Position-aware Rally Progress and Player Styles Fusion for Stroke Forecasting in Badminton (AAAI 2022) Official code of the paper ShuttleN

Milano (This is a research project, not an official NVIDIA product.) Documentation https://nvidia.github.io/Milano Milano (Machine learning autotuner

DeepSpeed+Megatron trained the world's most powerful language model: MT-530B DeepSpeed is hiring, come join us! DeepSpeed is a deep learning optimizat

Minimal-IK A simple and naive inverse kinematics solver for MANO hand model, SMPL body model, and SMPL-H body+hand model. Briefly, given joint coordin

MixRNet(Using mixup as regularization and tuning hyper-parameters for ResNets) Using mixup data augmentation as reguliraztion and tuning the hyper par

TSCV: Time Series Cross-Validation This repository is a scikit-learn extension for time series cross-validation. It introduces gaps between the traini

Fast Pattern Fetcher (fpf) Coded with 3 by HS Devansh Raghav Fast Pattern Fetcher, Takes a URLs list and outputs the URLs which contains the paramete

Sample-specific Bayesian Networks A framework for estimating the structures and parameters of Bayesian networks (DAGs) at per-sample or per-patient re

Identifying Stroke Indicators Using Rough Sets With the spirit of reproducible research, this repository contains all the codes required to produce th

Paint Transformer: Feed Forward Neural Painting with Stroke Prediction [Paper] [Official Paddle Implementation] [Huggingface Gradio Demo] [Unofficial

DINN We introduce Disease Informed Neural Networks (DINNs) — neural networks capable of learning how diseases spread, forecasting their progression, a

AISD Acute ischemic stroke dataset contains 397 Non-Contrast-enhanced CT (NCCT) scans of acute ischemic stroke with the interval from symptom onset to

Small Lesion Segmentation in Brain MRIs with Subpixel Embedding PyTorch implementation of Small Lesion Segmentation in Brain MRIs with Subpixel Embedd

openmc-plasma-source This python-based package offers a way of creating a parametric OpenMC plasma source from plasma parameters. The OpenMC sources a

Paint Transformer: Feed Forward Neural Painting with Stroke Prediction [Paper] [PaddlePaddle Implementation] Homepage of paper: Paint Transformer: Fee

Efficient Neural Architecture Search (ENAS) in PyTorch PyTorch implementation of Efficient Neural Architecture Search via Parameters Sharing. ENAS red

StrokeStrip: Joint Parameterization and Fitting of Stroke Clusters Dave Pagurek van Mossel1, Chenxi Liu1, Nicholas Vining1,2, Mikhail Bessmeltsev3, Al

The tool helps to find hidden parameters that can be vulnerable or can reveal interesting functionality that other hunters miss. Greater accuracy is achieved thanks to the line-by-line comparison of pages, comparison of response code and reflections.

Official PyTorch implementation of the preprint paper "Stylized Neural Painting", accepted to CVPR 2021.

ASMA-GAN Anisotropic Stroke Control for Multiple Artists Style Transfer Proceedings of the 28th ACM International Conference on Multimedia The officia

It selects the best indexing parameters to achieve the highest recalls given memory and query speed constraints.

DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective.

[Unofficial code-base] NeRF--: Neural Radiance Fields Without Known Camera Parameters [ Project | Paper | Official code base ] ⬅️ Thanks the original

Token Labeling: Training an 85.4% Top-1 Accuracy Vision Transformer with 56M Parameters on ImageNet (arxiv) This is a Pytorch implementation of our te

NeRF--: Neural Radiance Fields Without Known Camera Parameters Project Page | Arxiv | Colab Notebook | Data Zirui Wang¹, Shangzhe Wu², Weidi Xie², Min

Emily's Symbol Dictionary Design This dictionary was created with the following goals in mind: Have a consistent method to type (pretty much) every sy

Guide: Finetune GPT2-XL (1.5 Billion Parameters) and GPT-NEO (2.7 Billion Parameters) on a single 16 GB VRAM V100 Google Cloud instance with Huggingfa

The mljar-supervised is an Automated Machine Learning Python package that works with tabular data. I

DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective. 10x Larger Models 10x Faster Trainin

BurpParamFlagger A Burp extension adding a passive scan check to flag parameters whose name or value may indicate a possible insertion point for SSRF

Flake8 Builtins plugin Check for python builtins being used as variables or parameters. Imagine some code like this: def max_values(list, list2):

Param Param is a library providing Parameters: Python attributes extended to have features such as type and range checking, dynamically generated valu

GPT-NeoX An implementation of model parallel GPT-3-like models on GPUs, based on the DeepSpeed library. Designed to be able to train models in the hun

MLJAR Automated Machine Learning Documentation: https://supervised.mljar.com/ Source Code: https://github.com/mljar/mljar-supervised Table of Contents