data-to-paper: AI-driven scientific research
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Updated
May 20, 2024 - Python
data-to-paper: AI-driven scientific research
Machine Learning for Computer Security
Peax is a tool for interactive visual pattern search and exploration in epigenomic data based on unsupervised representation learning with autoencoders
Interesting resources related to Explainable Artificial Intelligence, Interpretable Machine Learning, Interactive Machine Learning, Human in Loop and Visual Analytics.
Tornado is an open source Human-in-the-loop machine learning tool. It helps you label your dataset on the fly while training your model through a simple web user interface. It supports all data types: structured, text and image.
Interactive Neural Machine Translation tool
RootPainter: Deep Learning Segmentation of Biological Images with Corrective Annotation
A system for building labeling tools
Personalized Training for the Sequence Learning task with the NAO robot and the MUSE EEG sensor
RapidLib is a lightweight library for interactive machine learning.
RootPainter3D: Interactive-machine-learning enables rapid and accurate contouring for radiotherapy
Interactive multimedia captioning with Keras
Rough set and machine learning data structures, algorithms and tools, including algorithms for discernibility matrix, reducts, decision rules, classification (RoughSet, KNN, RIONIDA, AQ15, C4.5, SVM, NeuralNetwork and many others), discretization (1R, Entropy Minimization, ChiMerge, MD), and tool for interactive and explainable machine learning.
Tölvera is a library for exploring musical performance with artificial life (ALife) and self-organising systems.
Paper list of Interactive Labeling Algorithm
RapidLib is a lightweight library for interactive machine learning. Bela is a platform for interactive sensor and audio processing.
User Modelling for Avoiding Overfitting in Interactive Knowledge Elicitation for Prediction
Risk Factor Analysis for Medical Data, Open-source Machine Learning Platform
Group project at Augsburg University
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