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Yanjun Qi / Jane's Projects

amazon-sagemaker-examples icon amazon-sagemaker-examples

Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.

blue_benchmark icon blue_benchmark

BLUE benchmark consists of five different biomedicine text-mining tasks with ten corpora.

covid-sanity icon covid-sanity

Aspires to help the influx of bioRxiv / medRxiv papers on COVID-19

covid19-review icon covid19-review

A collaborative review of the emerging COVID-19 literature. Join the chat here:

dada icon dada

The official code for DADA: Differentiable Automatic Data Augmentation

datamicroarray icon datamicroarray

A collection of small-sample, high-dimensional microarray data sets to assess machine-learning algorithms and models.

deep-review icon deep-review

A collaboratively written review paper on deep learning, genomics, and precision medicine

eraserbenchmark icon eraserbenchmark

A benchmark for understanding and evaluating rationales: http://www.eraserbenchmark.com/

evademl icon evademl

An evolutionary framework for evading machine learning-based malware classifiers.

examples icon examples

A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.

flair icon flair

A very simple framework for state-of-the-art Natural Language Processing (NLP)

fonduer icon fonduer

A knowledge base construction engine for richly formatted data

freia icon freia

Framework for Easily Invertible Architectures

haystack icon haystack

:mag: Transformers at scale for question answering & neural search. Using NLP via a modular Retriever-Reader-Pipeline. Supporting DPR, Elasticsearch, HuggingFace's Modelhub...

informer2020 icon informer2020

The GitHub repository for the paper "Informer" accepted by AAAI 2021.

medcat icon medcat

Medical Concept Annotation Tool

mmgeneration icon mmgeneration

MMGeneration is a powerful toolkit for generative models, based on PyTorch and MMCV.

neural-process-family icon neural-process-family

Code for the Neural Processes website and replication of 4 papers on NPs. Pytorch implementation.

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