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igsmines • Science 44%

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tbox • Science 26%

Random usefull toolbox

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yolov5_d415 • Science 44%

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docker-sod-new • Science 44%

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uqtestfuns • Science 67%

A Python3 library of uncertainty quantification (UQ) test functions. Mirror of the UQTestFuns repository. Please do not post issues or pull requests here. Use https://github.com/damar-wicaksono/uqtestfuns instead.

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astro-accelerate • Science 67%

AstroAccelerate is a many-core accelerated software package for processing time-domain radio-astronomy data.

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flashmm • Science 39%

Fast and Scalable Single Cell Differential Expression Analysis using Mixed-effects Models

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histomil • Science 44%

A Python package for handling histopathology whole-slide images using multiple instance learning (MIL) techniques.

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xactonomial • Science 13%

Exact Inference for Real-Valued Functionals of k-Sample Multinomial Parameters

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geogenr • Science 13%

Generator from American Community Survey (ACS) Geodatabases

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logitopp • Science 26%

An extension of mobiTopp for modeling parcel orders and their last-mile deliveries.

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tdmining • Science 26%

TDMINING Repo

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transformers--clipseg • Science 44%

This is the code to train CLIPSeg based on hugging face transformers

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medical_gpt • Science 44%

模型介绍和我的huggingface地址: 1.About medical_gpt: Training Your Own medical_gpt Model with ChatGPT Training Pipeline. 训练医疗大模型,实现了包括增量预训练、有监督微调、RLHF(奖励建模、强化学习训练)和DPO(直接偏好优化)。2.https://huggingface.co/shancx

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marferret • Science 75%

Code repository for collection, ingestion, and processing of genomic and transcriptomic sequence data into a reproducible reference sequence database

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fiesta • Science 26%

FIESTA (Forest Inventory ESTimation and Analysis) is a research estimation tool for analysts that work with sample-based inventory data from the U.S. Department of Agriculture, Forest Service, Forest Inventory and Analysis (FIA) Program. Follow the link below for more information:

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tictactoe-ai • Science 44%

Tic Tac Toe AIs developed for MAP4112 at UCF

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semi-discrete-scheme-for-kirchhoff-eqn • Science 67%

This is the numerical implementation section of our preprint, which has been submitted to arXiv under the identifier arXiv:2303.10350.

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popinf • Science 23%

Assumption-Lean and Data-Adaptive Post-Prediction Inference

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onderzoek • Science 44%

In deze repository staan de gebruikte Python scripts om de read/write speeds te berekenen