Python Segmetation-benchmarks Resources

M1, M1 Pro, M1 Max Machine Learning Speed Test Comparison This repo contains some sample code to benchmark the new M1 MacBooks (M1 Pro and M1 Max) aga

This repo is for the paper: Theory-inspired Parameter Control Benchmarks for Dynamic Algorithm Configuration The DAC environment is based on the Dynam

convnet-benchmarks Easy benchmarking of all public open-source implementations of convnets. A summary is provided in the section below. Machine: 6-cor

Best-practice-for-network-segmentation What is this? This project was created to publish the best practices for segmentation of the corporate network

Code For the Paper "Understanding Entropy Coding With Asymmetric Numeral Systems (ANS): a Statistician's Perspective" Author: Robert Bamler Date: 22 D

TensorFlow benchmarks This repository contains various TensorFlow benchmarks. Currently, it consists of two projects: PerfZero: A benchmark framework

The CodeSearchNet challenge has been concluded We would like to thank all participants for their submissions and we hope that this challenge provided

Design-Bench Design-Bench is a benchmarking framework for solving automatic design problems that involve choosing an input that maximizes a black-box

benchmark_spaces Benchmarks of how well different two dimensional spaces work fo

Rust Markdown Parsing Benchmarks This repo tries to assess Rust markdown parsing

Raster processing benchmarks This repository contains a collection of raster processing benchmarks for Python and R packages. The tests cover the most

Benchmarks for Object Detection in Aerial Images

PyTorch implementation of Video Transformer Benchmarks This repository is mainly built upon Pytorch and Pytorch-Lightning. We wish to maintain a colle

ClimART - A Benchmark Dataset for Emulating Atmospheric Radiative Transfer in Weather and Climate Models Official PyTorch Implementation Using deep le

Power Grid Lib - Optimal Power Flow This benchmark library is curated and maintained by the IEEE PES Task Force on Benchmarks for Validation of Emergi

Self-Supervised Policy Adaptation during Deployment PyTorch implementation of PAD and evaluation benchmarks from Self-Supervised Policy Adaptation dur

PopMark Just a little benchmark for scrapper PC's This benchmark is for old computer that dont support other benchmark because of support. Like lack o

AP-10K: A Benchmark for Animal Pose Estimation in the Wild Introduction | Updates | Overview | Download | Training Code | Key Questions | License Intr

Face Recognition: Too Bias, or Not Too Bias? Robinson, Joseph P., Gennady Livitz, Yann Henon, Can Qin, Yun Fu, and Samson Timoner. "Face recognition:

Application-Oriented Performance Benchmarks for Quantum Computing This repository contains a collection of prototypical application- or algorithm-cent

Spanish Language Models 💃🏻 A repository part of the MarIA project. Corpora 📃 Corpora Number of documents Number of tokens Size (GB) BNE 201,080,084

Large Scale Learning on Non-Homophilous Graphs: New Benchmarks and Strong Simple Methods Large Scale Learning on Non-Homophilous Graphs: New Benchmark

Variance-Aware-MT-Test-Sets Variance-Aware Machine Translation Test Sets License See LICENSE. We follow the data licensing plan as the same as the WMT

Datasets | Website | Raw Data | OpenReview SustainBench: Benchmarks for Monitoring the Sustainable Development Goals with Machine Learning Christopher

FIW Data Development Kit Table of Contents Introduction Families In the Wild Database Publications Organization To Do License Getting Involved Introdu

Large Scale Learning on Non-Homophilous Graphs: New Benchmarks and Strong Simple Methods Large Scale Learning on Non-Homophilous Graphs: New Benchmark

BalancingGroups Code to replicate the experimental results from Simple data balancing baselines achieve competitive worst-group-accuracy. Replicating

A suite of benchmarks for CPU and GPU performance of the most popular high-performance libraries for Python :rocket:

BalancingGroups Code to replicate the experimental results from Simple data balancing baselines achieve competitive worst-group-accuracy. Replicating

Physion: Evaluating Physical Prediction from Vision in Humans and Machines This repo contains code and data to reproduce the results in our paper, Phy

Open-source library for reliable evaluation on reinforcement learning and machine learning benchmarks. See NeurIPS 2021 oral for details.

Parquet benchmarks This repository contains a set of benchmarks of different implementations of Parquet (storage format) - Arrow (in-memory format).

Nvim.Bench Reproducible nvim completion framework benchmarks. Runs inside Docker. Fair and balanced Methodology Note: for all "randomness", they are g

Sequence Modeling Benchmarks and Temporal Convolutional Networks (TCN) This repository contains the experiments done in the work An Empirical Evaluati

Silero Models: pre-trained speech-to-text, text-to-speech models and benchmarks made embarrassingly simple

wireguard-config-benchmark is a python script that benchmarks the download speeds for the connections defined in one or more wireguard config files. If multiple configs are benchmarked it will output a file ranking them from fastest to slowest.

FedLab-benchmarks This repo contains standard implementations of FedLab and its provided benchmarks. Currently, following algorithms or benchrmarks ar

Sequence Modeling Benchmarks and Temporal Convolutional Networks (TCN) This repository contains the experiments done in the work An Empirical Evaluati

Spanish Language Models 💃🏻 Corpora 📃 Corpora Number of documents Size (GB) BNE 201,080,084 570GB Models 🤖 RoBERTa-base BNE: https://huggingface.co

Semi-Supervised Domain Generalization This code is the official implementation of the following paper: Semi-Supervised Domain Generalization with Stoc

TSForecasting This repository contains the implementations related to the experiments of a set of publicly available datasets that are used in the tim

NAS-Bench-301 This repository containts code for the paper: "NAS-Bench-301 and the Case for Surrogate Benchmarks for Neural Architecture Search". The

New Benchmarks for Learning on Non-Homophilous Graphs Here are the codes and datasets accompanying the paper: New Benchmarks for Learning on Non-Homop

NeurIPS 2020 SEVIR Code for paper: SEVIR : A Storm Event Imagery Dataset for Deep Learning Applications in Radar and Satellite Meteorology Requirement