A highly scalable and accurate inference of gene expression and structure for single-cell transcriptomes using semi-supervised deep learning.
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Updated
May 19, 2021 - HTML
A highly scalable and accurate inference of gene expression and structure for single-cell transcriptomes using semi-supervised deep learning.
A little lab of learning algorithms (in LUA). Less XAI, but better
A highly scalable and accurate inference of gene expression and structure for single-cell transcriptomes using semi-supervised deep learning.
Partial Label Learning based on GMM
noisy labels; missing labels; semi-supervised learning; entropy; uncertainty; robustness and generalisation.
Interactively create machine learning datasets using facets visualization tool and active learning or semi-supervised learning. Visualizations for machine learning datasets
To avoid some common AI sins, find explicable models using minimal data (via tuned learners).
Using Semi Supervised Learning for Retinal Cyst Segmentation
Look around a little. Catch good stuff.
Reimplementation of mix match algorithm using fast.ai
This repo contains code for uisng semi-supervised contrastive learning to learn phenotypical representations from Cell Painting image data
Poor inventory management leads to a loss in sales which in turn paints an inaccurate picture of lower demand for certain items, making future order predictions based on that past data inherently inaccurate. Instead, smart retailers use real-time data to move inventory where it’s needed before it’s too late. Additionally, they use predictive ana…
Explore the impact of training data size on sentiment analysis model performance using weak labels and transfer learning
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