[PDF][PDF] Accelerating t-SNE using tree-based algorithms
L Van Der Maaten - The journal of machine learning research, 2014 - jmlr.org
The paper investigates the acceleration of t-SNE—an embedding technique that is
commonly used for the visualization of high-dimensional data in scatter plots—using two …
commonly used for the visualization of high-dimensional data in scatter plots—using two …
CAR T cell manufacturing from naive/stem memory T lymphocytes enhances antitumor responses while curtailing cytokine release syndrome
S Arcangeli, C Bove, C Mezzanotte… - The Journal of …, 2022 - Am Soc Clin Investig
Chimeric antigen receptor (CAR) T cell expansion and persistence represent key factors to
achieve complete responses and prevent relapses. These features are typical of early …
achieve complete responses and prevent relapses. These features are typical of early …
Disrupting N-glycan expression on tumor cells boosts chimeric antigen receptor T cell efficacy against solid malignancies
B Greco, V Malacarne, F De Girardi, GM Scotti… - Science translational …, 2022 - science.org
Immunotherapy with chimeric antigen receptor (CAR)–engineered T cells showed
exceptional successes in patients with refractory B cell malignancies. However, first-in …
exceptional successes in patients with refractory B cell malignancies. However, first-in …
Interpretable dimensionality reduction of single cell transcriptome data with deep generative models
Single-cell RNA-sequencing has great potential to discover cell types, identify cell states,
trace development lineages, and reconstruct the spatial organization of cells. However …
trace development lineages, and reconstruct the spatial organization of cells. However …
Indefinite proximity learning: A review
Efficient learning of a data analysis task strongly depends on the data representation. Most
methods rely on (symmetric) similarity or dissimilarity representations by means of metric …
methods rely on (symmetric) similarity or dissimilarity representations by means of metric …
Approximated and user steerable tSNE for progressive visual analytics
Progressive Visual Analytics aims at improving the interactivity in existing analytics
techniques by means of visualization as well as interaction with intermediate results. One …
techniques by means of visualization as well as interaction with intermediate results. One …
Data visualization by nonlinear dimensionality reduction
A Gisbrecht, B Hammer - Wiley Interdisciplinary Reviews: Data …, 2015 - Wiley Online Library
In this overview, commonly used dimensionality reduction techniques for data visualization
and their properties are reviewed. Thereby, the focus lies on an intuitive understanding of …
and their properties are reviewed. Thereby, the focus lies on an intuitive understanding of …
Deepeyes: Progressive visual analytics for designing deep neural networks
Deep neural networks are now rivaling human accuracy in several pattern recognition
problems. Compared to traditional classifiers, where features are handcrafted, neural …
problems. Compared to traditional classifiers, where features are handcrafted, neural …
Bone marrow central memory and memory stem T-cell exhaustion in AML patients relapsing after HSCT
M Noviello, F Manfredi, E Ruggiero, T Perini… - Nature …, 2019 - nature.com
The major cause of death after allogeneic Hematopoietic Stem Cell Transplantation (HSCT)
for acute myeloid leukemia (AML) is disease relapse. We investigated the expression of …
for acute myeloid leukemia (AML) is disease relapse. We investigated the expression of …
Parametric nonlinear dimensionality reduction using kernel t-SNE
Novel non-parametric dimensionality reduction techniques such as t-distributed stochastic
neighbor embedding (t-SNE) lead to a powerful and flexible visualization of high …
neighbor embedding (t-SNE) lead to a powerful and flexible visualization of high …