59 Repositories
Python average-precision Libraries
Precision Medicine Knowledge Graph (PrimeKG)
PrimeKG Website | bioRxiv Paper | Harvard Dataverse Precision Medicine Knowledge Graph (PrimeKG) presents a holistic view of diseases. PrimeKG integra
This initial strategy was developed specifically for larger pools and is based on taking a moving average and deriving Bollinger Bands to create a projected active liquidity range.
Gamma's Strategy One This initial strategy was developed specifically for larger pools and is based on taking a moving average and deriving Bollinger
code for paper"A High-precision Semantic Segmentation Method Combining Adversarial Learning and Attention Mechanism"
PyTorch implementation of UAGAN(U-net Attention Generative Adversarial Networks) This repository contains the source code for the paper "A High-precis
Official code release for: EditGAN: High-Precision Semantic Image Editing
Official code release for: EditGAN: High-Precision Semantic Image Editing
Object detection evaluation metrics using Python.
Object detection evaluation metrics using Python.
Client-Server design (guess the closest number to the average score game)
Multiplayer game (enter the number closest to the average) Design Client-Server design The client's side is responsible for sending numbers from the g
Projecting interval uncertainty through the discrete Fourier transform
Projecting interval uncertainty through the discrete Fourier transform This repo
Exposure Time Calculator (ETC) and radial velocity precision estimator for the Near InfraRed Planet Searcher (NIRPS) spectrograph
NIRPS-ETC Exposure Time Calculator (ETC) and radial velocity precision estimator for the Near InfraRed Planet Searcher (NIRPS) spectrograph February 2
Using Logistic Regression and classifiers of the dataset to produce an accurate recall, f-1 and precision score
Using Logistic Regression and classifiers of the dataset to produce an accurate recall, f-1 and precision score
A commany has recently introduced a new type of bidding, the average bidding, as an alternative to the bid given to the current maximum bidding
Business Problem A commany has recently introduced a new type of bidding, the average bidding, as an alternative to the bid given to the current maxim
Intel® Neural Compressor is an open-source Python library running on Intel CPUs and GPUs
Intel® Neural Compressor targeting to provide unified APIs for network compression technologies, such as low precision quantization, sparsity, pruning, knowledge distillation, across different deep learning frameworks to pursue optimal inference performance.
A small Python library which gives you the IEEE-754 representation of a floating point number.
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
Scalene: a high-performance, high-precision CPU, GPU, and memory profiler for Python
Scalene: a high-performance CPU, GPU and memory profiler for Python by Emery Berger, Sam Stern, and Juan Altmayer Pizzorno. Scalene community Slack Ab
Most popular metrics used to evaluate object detection algorithms.
Most popular metrics used to evaluate object detection algorithms.
Python library for ODE integration via Taylor's method and LLVM
heyoka.py Modern Taylor's method via just-in-time compilation Explore the docs » Report bug · Request feature · Discuss The heyókȟa [...] is a kind of
Implementation of our paper "DMT: Dynamic Mutual Training for Semi-Supervised Learning"
DMT: Dynamic Mutual Training for Semi-Supervised Learning This repository contains the code for our paper DMT: Dynamic Mutual Training for Semi-Superv
A PyTorch Extension: Tools for easy mixed precision and distributed training in Pytorch
Introduction This is a Python package available on PyPI for NVIDIA-maintained utilities to streamline mixed precision and distributed training in Pyto
Tracking (of choice) cryptocurrencies' daily prices and moving average.
Crypto-price-moving_average Tracking (of choice) cryptocurrencies' daily prices and moving average. About Alpha Vantage The Alpha Vantage library (htt
Average Clicker Game (AVG) is a Python made game using tkinter
Average-Clicker-Game Average Clicker Game (AVG) is a Python clicker game not made with pygame but with tkinter, it has worker, worker upgrades, times
Robustness between the worst and average case
Robustness between the worst and average case A repository that implements intermediate robustness training and evaluation from the NeurIPS 2021 paper
Robustness between the worst and average case
Robustness between the worst and average case A repository that implements intermediate robustness training and evaluation from the NeurIPS 2021 paper
Code repository for "Reducing Underflow in Mixed Precision Training by Gradient Scaling" presented at IJCAI '20
Reducing Underflow in Mixed Precision Training by Gradient Scaling This project implements the gradient scaling method to improve the performance of m
Usos Semester average helper
Usos Semester average helper Dzieki temu skryptowi mozesz sprawdzic srednia ocen na kazdy odbyty przez ciebie semestr PARAMETERS required: '--username
Modified GPT using average pooling to reduce the softmax attention memory constraints.
NLP-GPT-Upsampling This repository contains an implementation of Open AI's GPT Model. In particular, this implementation takes inspiration from the Ny
Given an array of integers, calculate the ratios of its elements that are positive, negative, and zero.
Given an array of integers, calculate the ratios of its elements that are positive, negative, and zero. Print the decimal value of each fraction on a new line with places after the decimal.
Quantization library for PyTorch. Support low-precision and mixed-precision quantization, with hardware implementation through TVM.
HAWQ: Hessian AWare Quantization HAWQ is an advanced quantization library written for PyTorch. HAWQ enables low-precision and mixed-precision uniform
Fcpy: A Python package for high performance, fast convergence and high precision numerical fractional calculus computing.
Fcpy: A Python package for high performance, fast convergence and high precision numerical fractional calculus computing.
Official PyTorch implementation for "Low Precision Decentralized Distributed Training with Heterogenous Data"
Low Precision Decentralized Training with Heterogenous Data Official PyTorch implementation for "Low Precision Decentralized Distributed Training with
reXmeX is recommender system evaluation metric library.
A general purpose recommender metrics library for fair evaluation.
Single machine, multiple cards training; mix-precision training; DALI data loader.
Template Script Category Description Category script comparison script train.py, loader.py for single-machine-multiple-cards training train_DP.py, tra
Here I plotted data for the average test scores across schools and class sizes across school districts.
HW_02 Here I plotted data for the average test scores across schools and class sizes across school districts. Average Test Score by Race This graph re
Implementation of average- and worst-case robust flatness measures for adversarial training.
Relating Adversarially Robust Generalization to Flat Minima This repository contains code corresponding to the MLSys'21 paper: D. Stutz, M. Hein, B. S
Average time per match by division
HW_02 Unzip matches.rar to access .json files for matches. Get an API key to access their data at: https://developer.riotgames.com/ Average time per m
Definition of a business problem according to Wilson Lower Bound Score and Time Based Average Rating
Wilson Lower Bound Score, Time Based Rating Average In this study I tried to calculate the product rating and sorting reviews more accurately. I have
Python Image Morpher (PIM) is a program that can take two images and blend them to whatever extent or precision that you like
Python Image Morpher (PIM) is a program that can take two images and blend them to whatever extent or precision that you like! It is designed to emulate some of Python's OpenCV image processing from scratch without reference.
A lightweight wrapper for PyTorch that provides a simple declarative API for context switching between devices, distributed modes, mixed-precision, and PyTorch extensions.
A lightweight wrapper for PyTorch that provides a simple declarative API for context switching between devices, distributed modes, mixed-precision, and PyTorch extensions.
A CRM department in a local bank works on classify their lost customers with their past datas. So they want predict with these method that average loss balance and passive duration for future.
Rule-Based-Classification-in-a-Banking-Case. A CRM department in a local bank works on classify their lost customers with their past datas. So they wa
Ebay Webscraper for Getting Average Product Price
Ebay-Webscraper-for-Getting-Average-Product-Price The code in this repo is used to determine the average price of an item on Ebay given a valid search
This is the pytorch implementation for the paper: Generalizable Mixed-Precision Quantization via Attribution Rank Preservation, which is accepted to ICCV2021.
GMPQ: Generalizable Mixed-Precision Quantization via Attribution Rank Preservation This is the pytorch implementation for the paper: Generalizable Mix
Provide partial dates and retain the date precision through processing
Prefix date parser This is a helper class to parse dates with varied degrees of precision. For example, a data source might state a date as 2001, 2001
EdMIPS: Rethinking Differentiable Search for Mixed-Precision Neural Networks
EdMIPS is an efficient algorithm to search the optimal mixed-precision neural network directly without proxy task on ImageNet given computation budgets. It can be applied to many popular network architectures, including ResNet, GoogLeNet, and Inception-V3.
A Python package for floating-point binary fractions. Do math in base 2!
An implementation of a floating-point binary fractions class and module in Python. Work with binary fractions and binary floats with ease!
JMP is a Mixed Precision library for JAX.
Mixed precision training [0] is a technique that mixes the use of full and half precision floating point numbers during training to reduce the memory bandwidth requirements and improve the computational efficiency of a given model.
A simple way to train and use PyTorch models with multi-GPU, TPU, mixed-precision
🤗 Accelerate was created for PyTorch users who like to write the training loop of PyTorch models but are reluctant to write and maintain the boilerplate code needed to use multi-GPUs/TPU/fp16.
OHLC Average Prediction of Apple Inc. Using LSTM Recurrent Neural Network
Stock Price Prediction of Apple Inc. Using Recurrent Neural Network OHLC Average Prediction of Apple Inc. Using LSTM Recurrent Neural Network Dataset:
buys ethereum based on graphics card moving average price on ebay
ebay_trades buys ethereum based on graphics card moving average price on ebay Built as a meme, this application will scrape the first 3 pages of ebay
Simple Pose: Rethinking and Improving a Bottom-up Approach for Multi-Person Pose Estimation
SimplePose Code and pre-trained models for our paper, “Simple Pose: Rethinking and Improving a Bottom-up Approach for Multi-Person Pose Estimation”, a
[ICLR 2021] "CPT: Efficient Deep Neural Network Training via Cyclic Precision" by Yonggan Fu, Han Guo, Meng Li, Xin Yang, Yining Ding, Vikas Chandra, Yingyan Lin
CPT: Efficient Deep Neural Network Training via Cyclic Precision Yonggan Fu, Han Guo, Meng Li, Xin Yang, Yining Ding, Vikas Chandra, Yingyan Lin Accep
Scikit-learn compatible estimation of general graphical models
skggm : Gaussian graphical models using the scikit-learn API In the last decade, learning networks that encode conditional independence relationships
A PyTorch Extension: Tools for easy mixed precision and distributed training in Pytorch
Introduction This repository holds NVIDIA-maintained utilities to streamline mixed precision and distributed training in Pytorch. Some of the code her
CDIoU and CDIoU loss is like a convenient plug-in that can be used in multiple models. CDIoU and CDIoU loss have different excellent performances in several models such as Faster R-CNN, YOLOv4, RetinaNet and . There is a maximum AP improvement of 1.9% and an average AP of 0.8% improvement on MS COCO dataset, compared to traditional evaluation-feedback modules. Here we just use as an example to illustrate the code.
CDIoU-CDIoUloss CDIoU and CDIoU loss is like a convenient plug-in that can be used in multiple models. CDIoU and CDIoU loss have different excellent p
Monocular Depth Estimation - Weighted-average prediction from multiple pre-trained depth estimation models
merged_depth runs (1) AdaBins, (2) DiverseDepth, (3) MiDaS, (4) SGDepth, and (5) Monodepth2, and calculates a weighted-average per-pixel absolute dept
A PyTorch Extension: Tools for easy mixed precision and distributed training in Pytorch
This repository holds NVIDIA-maintained utilities to streamline mixed precision and distributed training in Pytorch. Some of the code here will be included in upstream Pytorch eventually. The intention of Apex is to make up-to-date utilities available to users as quickly as possible.
HandTailor: Towards High-Precision Monocular 3D Hand Recovery
HandTailor This repository is the implementation code and model of the paper "HandTailor: Towards High-Precision Monocular 3D Hand Recovery" (arXiv) G
Source code for Acorn, the precision farming rover by Twisted Fields
Acorn precision farming rover This is the software repository for Acorn, the precision farming rover by Twisted Fields. For more information see twist
Scikit-learn compatible estimation of general graphical models
skggm : Gaussian graphical models using the scikit-learn API In the last decade, learning networks that encode conditional independence relationships
Code for "High-Precision Model-Agnostic Explanations" paper
Anchor This repository has code for the paper High-Precision Model-Agnostic Explanations. An anchor explanation is a rule that sufficiently “anchors”
BitPack is a practical tool to efficiently save ultra-low precision/mixed-precision quantized models.
BitPack is a practical tool that can efficiently save quantized neural network models with mixed bitwidth.
Scalene: a high-performance, high-precision CPU and memory profiler for Python
scalene: a high-performance CPU and memory profiler for Python by Emery Berger 中文版本 (Chinese version) About Scalene % pip install -U scalene Scalen