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EmbryoNet_Drug-screen_BML-2840
This dataset contains the drugscreen of the known bioactives library (Enzo Screen Well BML 2840) including the imaging data (time lapse bright-field microscopy of zebrafish... -
EmbryoNet_Drug-screen_BML-2843
This dataset contains the drugscreen of the FDA-approved drug library (Enzo Screen Well BML 2843, Plates 1-2) including the imaging data (time lapse bright-field microscopy) and... -
Dataset: input and results related to the paper 'Anticipointment detection in...
This dataset features the training models, emotion classifications and emotion patterns before and after events, related to the paper: F. Kunneman, M. van Mulken and A. Van den... -
EGOFALLS: A visual-audio dataset and benchmark for fall detection using egoce...
We've provided a readme.pdf to explain how to use the dataset. Here, we reiterate some of that information to assist others in utilizing the dataset. Please be aware that the... -
sdaas - a Python tool computing an amplitude anomaly score of seismic data an...
The increasingly high number of big data applications in seismology has made quality control tools to filter, discard, or rank data of extreme importance. In this framework,... -
Remote Early Detection of SARS-CoV-2 infections (COVID-RED)
Rationale: The World Health Organization (WHO) has declared the current coronavirus disease (COVID-19) outbreak, caused by the SARS-CoV-2 virus, to be a pandemic and,... -
3-digit occupation code images from the Norwegian census of 1950 - Manual rev...
This dataset is made up of images containing handwritten 3-digit occupation codes from the Norwegian population census of 1950. The occupation codes were added to the census... -
Wild-Anim Dataset
The Wild-Anim dataset available from this page consists of 5 classes that contains uniformly distributed images examples of wild animals. In total, the dataset contains 5000... -
Thermomechanical properties of honeycomb lattices from internal-coordinates p...
Lattice dynamics in low-dimensional materials and, in particular, the quadratic behaviour of the flexural acoustic modes play a fundamental role in their thermomechanical and... -
Thermomechanical properties of honeycomb lattices from internal-coordinates p...
Lattice dynamics in low-dimensional materials and, in particular, the quadratic behaviour of the flexural acoustic modes play a fundamental role in their thermomechanical... -
Synthesis of Metal-Organic Frameworks: capturing chemical intuition
We report a methodology using machine learning to capture chemical intuition from a set of (partially) failed attempts to synthesize a metal organic framework. We define... -
Phase-only holograms and captured photographs
This dataset includes phase-only holograms optimized using an ideal holographic light transport model in the near field (Fresnel approximation). The dataset also includes... -
Electronic structure calculations of twisted multi-layer graphene superlattices
Quantum confinement endows two-dimensional (2D) layered materials with exceptional physics and novel properties compared to their bulk counterparts. Although certain two- and... -
Gaussian Approximation Potentials for iron from extended first-principles dat...
Interatomic potentials are often necessary to describe complex realistic systems that would be too costly to study from first-principles. Commonly, interatomic potentials are... -
Capturing chemical intuition in synthesis of metal-organic frameworks
We report a methodology using machine learning to capture chemical intuition from a set of (partially) failed attempts to synthesize a metal organic framework. We define... -
Capturing chemical intuition in synthesis of metal-organic frameworks
We report a methodology using machine learning to capture chemical intuition from a set of (partially) failed attempts to synthesize a metal organic framework. We define... -
CA-9, a dataset of carbon allotropes for training and testing of neural netwo...
The use of machine learning to accelerate computer simulations is on the rise. In atomistic simulations, the use of machine learning interatomic potentials (ML-IAPs) can... -
Capturing chemical intuition in synthesis of metal-organic frameworks
We report a methodology using machine learning to capture chemical intuition from a set of (partially) failed attempts to synthesize a metal organic framework. We define... -
Gaussian Approximation Potentials for iron from extended first-principles dat...
Interatomic potentials are often necessary to describe complex realistic systems that would be too costly to study from first-principles. Commonly, interatomic potentials are... -
Benchmark data for: Machine Learning for geospatial vector data classification
Benchmark data for paper "Deep Learning for Classification Tasks on Geospatial Vector Polygons". Core of the data is in the six numpy zip files. Each numpy zip contains the...