data-to-paper: Backward-traceable AI-driven scientific research
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Updated
Nov 25, 2024 - Python
data-to-paper: Backward-traceable AI-driven scientific research
Machine Learning for Computer Security
Interesting resources related to Explainable Artificial Intelligence, Interpretable Machine Learning, Interactive Machine Learning, Human in Loop and Visual Analytics.
Peax is a tool for interactive visual pattern search and exploration in epigenomic data based on unsupervised representation learning with autoencoders
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.
RootPainter: Deep Learning Segmentation of Biological Images with Corrective Annotation
Interactive Neural Machine Translation tool
Tölvera is a creative medium inspired by artificial life and self-organising systems.
An Interactive Machine Learning Toolkit
A system for building labeling tools
RapidLib is a lightweight library for interactive machine learning.
RootPainter3D: Interactive-machine-learning enables rapid and accurate contouring for radiotherapy
Personalized Training for the Sequence Learning task with the NAO robot and the MUSE EEG sensor
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.
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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