[HTML][HTML] Machine learning in python: Main developments and technology trends in data science, machine learning, and artificial intelligence
Smarter applications are making better use of the insights gleaned from data, having an
impact on every industry and research discipline. At the core of this revolution lies the tools …
impact on every industry and research discipline. At the core of this revolution lies the tools …
[HTML][HTML] The art of using t-SNE for single-cell transcriptomics
Single-cell transcriptomics yields ever growing data sets containing RNA expression levels
for thousands of genes from up to millions of cells. Common data analysis pipelines include …
for thousands of genes from up to millions of cells. Common data analysis pipelines include …
Long short-term relation transformer with global gating for video captioning
Video captioning aims to generate a natural language sentence to describe the main
content of a video. Since there are multiple objects in videos, taking full exploration of the …
content of a video. Since there are multiple objects in videos, taking full exploration of the …
t-visne: Interactive assessment and interpretation of t-sne projections
A Chatzimparmpas, RM Martins… - IEEE transactions on …, 2020 - ieeexplore.ieee.org
t-Distributed Stochastic Neighbor Embedding (t-SNE) for the visualization of
multidimensional data has proven to be a popular approach, with successful applications in …
multidimensional data has proven to be a popular approach, with successful applications in …
Prediction of liquid chromatographic retention time with graph neural networks to assist in small molecule identification
The predicted liquid chromatographic retention times (RTs) of small molecules are not
accurate enough for wide adoption in structural identification. In this study, we used the …
accurate enough for wide adoption in structural identification. In this study, we used the …
[HTML][HTML] Interpretable deep learning uncovers cellular properties in label-free live cell images that are predictive of highly metastatic melanoma
Deep learning has emerged as the technique of choice for identifying hidden patterns in cell
imaging data but is often criticized as" black box." Here, we employ a generative neural …
imaging data but is often criticized as" black box." Here, we employ a generative neural …
GPU accelerated t-distributed stochastic neighbor embedding
Modern datasets and models are notoriously difficult to explore and analyze due to their
inherent high dimensionality and massive numbers of samples. Existing visualization …
inherent high dimensionality and massive numbers of samples. Existing visualization …
Global and local structure preserving GPU t-SNE methods for large-scale applications
Currently, the use of dimensionality reduction techniques such as t-distributed stochastic
neighbor embedding (t-SNE) to visualize data has become essential in dealing with large …
neighbor embedding (t-SNE) to visualize data has become essential in dealing with large …
ChemPlot, a Python library for chemical space visualization
M Cihan Sorkun, D Mullaj, JMVA Koelman… - Chemistry …, 2022 - Wiley Online Library
Visualizing chemical spaces streamlines the analysis of molecular datasets by reducing the
information to human perception level, hence it forms an integral piece of molecular …
information to human perception level, hence it forms an integral piece of molecular …
ChemPlot, a Python library for chemical space visualization
Visualizing chemical spaces streamlines the analysis of molecular datasets by reducing the
information to human perception level, hence it forms an integral piece of molecular …
information to human perception level, hence it forms an integral piece of molecular …