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Search results for machine learning reproducible research
machine-learning
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reproducible-research
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40 search results found
Metaflow
⭐
7,524
🚀 Build and manage real-life ML, AI, and data science projects with ease!
Sacred
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4,152
Sacred is a tool to help you configure, organize, log and reproduce experiments developed at IDSIA.
Evalai
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1,621
☁️ 🚀 📊 📈 Evaluating state of the art in AI
Pycil
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613
PyCIL: A Python Toolbox for Class-Incremental Learning
Sionna
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534
Sionna: An Open-Source Library for Next-Generation Physical Layer Research
Labnotebook
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528
LabNotebook is a tool that allows you to flexibly monitor, record, save, and query all your machine learning experiments.
Facil
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425
Framework for Analysis of Class-Incremental Learning with 12 state-of-the-art methods and 3 baselines.
Fglab
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207
Future Gadget Laboratory
Ten Rules Jupyter
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185
Ten Simple Rules for Writing and Sharing Computational Analyses in Jupyter Notebooks
Example Get Started
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160
Get started DVC project
Grand Challenge.org
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156
A platform for end-to-end development of machine learning solutions in biomedical imaging
Lamda Pilot
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134
🎉 PILOT: A Pre-trained Model-Based Continual Learning Toolbox
Steppy
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134
Lightweight, Python library for fast and reproducible experimentation 🔬
Zoo
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103
Reference implementations of popular Binarized Neural Networks
Openml R
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90
R package to interface with OpenML
Mimic Iv Data Pipeline
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90
A customizable pipeline for data extraction from MIMIC-IV.
Fgmachine
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66
Future Gadget Machine
Chembl Downloader
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55
Write reproducible code for getting and processing ChEMBL
Dun
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52
Code for "Depth Uncertainty in Neural Networks" (https://arxiv.org/abs/2006.08437)
Benchpress
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52
A Snakemake workflow to run and benchmark structure learning (a.k.a. causal discovery) algorithms for probabilistic graphical models.
Open Solution Googleai Object Detection
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46
Open solution to the Google AI Object Detection Challenge 🍁
Example Get Started Experiments
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33
Get started DVC project
Repro
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33
Repro is a library for easily running code from published papers via Docker.
Mlrhyperopt
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31
Easy Hyper Parameter Optimization with mlr and mlrMBO.
Polyaxon Quick Start
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29
A quick start project for polyaxon
Confidentlearning Reproduce
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26
Official data release to reproduce Confident Learning paper results
Hash Grid Encoding
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24
Pure PyTorch implementation of Nvidia's hash grid encoding: https://nvlabs.github.io/instant-ngp/
Braph 2
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24
BRAPH 2.0 is a comprehensive software package for the analysis and visualization of brain connectivity data, offering flexible customization, rich visualization capabilities, and a platform for collaboration in neuroscience research.
Diff Rt
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19
This repository contains code to reproduce some of the results from the paper Sionna RT: Differentiable Ray Tracing for Radio Propagation Modeling using the Sionna™ link-level simulator.
Publications
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16
IMS Machine Learning Lab publications.
Topcuoglu_ml_mbio_2020
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16
Best practices for applying machine learning to bacterial 16S rRNA gene sequencing data
Reproducible Video Denoising State Of The Art
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15
Collection of popular and reproducible video denoising works.
Mmdagg Paper
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14
Reproducibility code for MMD Aggregated Two-Sample Test, by Schrab, Kim, Albert, Laurent, Guedj and Gretton: https://arxiv.org/abs/2110.15073
Exprec
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12
Exprec records your experiments so you can compare different runs and easily reproduce results
Pymake
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12
An experiment control system for reproducible research
Ai Project Template
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9
Project layout for efficient AI for science
Wasota
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6
Tmleworkshop
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6
Targeted maximum likelihood estimation (TMLE) enables the integration of machine learning approaches in comparative effectiveness studies. It is a doubly robust method, making use of both the outcome model and propensity score model to generate an unbiased estimate as long as at least one of the models is correctly specified.
Ksdagg Paper
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6
Code for reproducible experiments presented in KSD Aggregated Goodness-of-fit Test. https://arxiv.org/abs/2202.00824 NeurIPS 2022
Rump
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5
A Reproducible Untargeted Metabolomics Data Processing Pipeline
Cbench
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5
News: we have moved this code to the CK framework:
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