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T-distributed stochastic neighbor embedding

Known as: T-Distributed Stochastic Neighbour Embedding, T-SNE 
t-distributed stochastic neighbor embedding (t-SNE) is a machine learning algorithm for dimensionality reduction developed by Laurens van der Maaten… 
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Related topics

Related topics

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BioinformaticsComputer securityDeeplearning4jDimensionality reduction

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2019
2019
Identification of Combustion Trajectories Using t-Distributed Stochastic Neighbor Embedding (t-SNE)
With increasing computational power, direct numerical and large eddy simulation (DNS and LES) of reacting flows with complex… 
2019
2019
Detection and classification of structural changes using t-distributed stochastic neighbor embedding
This work states a structural health monitoring strategy for detection and classification of structural changes. The proposed… 
2019
2019
Blast furnace condition data clustering based on combination of T-distributed stochastic neighbor embedding and spectral clustering
T-distributed stochastic neighbor embedding (t-SNE) dimension reduction technique are combined with Spectral clustering algorithm… 
2018
2018
Lecture 8 – t-Distributed Stochastic Neighbor Embedding
Today, we introduce the non-linear dimensionality reduction method t-distributed Stochastic Neighbor Embedding (tSNE), a method… 
2018
2018
Multilingual Semantic Cyberspace of Scientific Papers Based on WebVR Technology
In this paper we describe a cyberspace of scientific papers in which the most cited and significant documents are represented by… 
2018
2018
Deep Neural Maps
We introduce a new unsupervised representation learning and visualization using deep convolutional networks and self organizing… 
2017
2017
d 3 D-DESI imaging reveal the hidden metabolic heterogeneity of cancer †
Visual inspection of tumour tissues does not reveal the complex metabolic changes that differentiate cancer and its sub-types… 
2017
2017
Neoantigens in MDS Are Associated with Two Novel CD4+ T Cell Subsets and Improved Overall Survival
Background The immune system has been shown to be important in the pathophysiology of MDS. Adaptive immunity relies on T cells… 
2014
2014
Variable-activation and variable-input deep neural network for robust speech recognition
In a previous study, we proposed variable-component deep neural network (VCDNN) to improve the robustness of context-dependent… 
2010
2010
On the Role and Impact of the Metaparameters in t-distributed Stochastic Neighbor Embedding
Similarity-based embedding is a paradigm that recently gained interest in the field of nonlinear dimensionality reduction. It… 
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