#dimensionalityreduction — Public Fediverse posts

A linear-time alternative for Dimensionality Reduction and fast visualisation

https://medium.com/@roman.f/a-linear-time-alternative-to-t-sne-for-dimensionality-reduction-and-fast-visualisation-5cd1a7219d6f

#HackerNews #DimensionalityReduction #FastVisualisation #LinearTime #DataScience #MachineLearning

A linear-time alternative for Dimensionality Reduction and fast visualisation

https://medium.com/@roman.f/a-linear-time-alternative-to-t-sne-for-dimensionality-reduction-and-fast-visualisation-5cd1a7219d6f

#HackerNews #DimensionalityReduction #FastVisualisation #LinearTime #DataScience #MachineLearning

🧠 New comprehensive review on #LowDimensional #embeddings of #HighDimensional data. Discusses how #dimensionalityreduction helps visualizing, exploring, and #modeling #ComplexSystems. From #PCA to #tSNE, #UMAP & #NeuralNetworks: Excellent overview paper👌

🌍 https://arxiv.org/abs/2508.15929

#CompNeuro #MachineLearning #DataVisualization

🧠 New comprehensive review on #LowDimensional #embeddings of #HighDimensional data. Discusses how #dimensionalityreduction helps visualizing, exploring, and #modeling #ComplexSystems. From #PCA to #tSNE, #UMAP & #NeuralNetworks: Excellent overview paper👌

🌍 https://arxiv.org/abs/2508.15929

#CompNeuro #MachineLearning #DataVisualization

We just completed a new course on #DimensionalityReduction in #Neuroscience, and the full teaching material 🐍💻 is now freely available (CC BY 4.0 license):

🌍 https://www.fabriziomusacchio.com/blog/2024-10-24-dimensionality_reduction_in_neuroscience/

The course is designed to provide an introductory overview of the application of dimensionality reduction techniques for neuroscientists and data scientists alike, focusing on how to handle the increasingly high-dimensional datasets generated by modern neuroscience research.

#PythonTutorial #CompNeuro

These four #Python #tutorials introduce and discuss #PCA, #tsne, #factoranalysis, and #Autoencoder as powerful tools for #DimensionalityReduction:

🌍 https://www.fabriziomusacchio.com/blog/2023-06-16-pca_with_python/
🌍 https://www.fabriziomusacchio.com/blog/2023-06-12-tsne_vs_pca/
🌍 https://www.fabriziomusacchio.com/blog/2023-06-16-factoranalysis_with_python/
🌍 https://www.fabriziomusacchio.com/blog/2023-06-16-autoencoder_with_python/

Feel free to share, use and remix 😊🙏

#tutorial

By the way this is the original article that presents t-SNE. Published 11/2008
https://jmlr.org/papers/volume9/vandermaaten08a/vandermaaten08a.pdf
T-distributed stochastic neighbor embedding (t-SNE) is a statistical method for visualizing high-dimensional data in 2 or 3 dimensions.
#DataVisualization #tSNE #MachineLearning #DimensionalityReduction #DataScience #AI #DataAnalysis #DataAnalytics

By the way this is the original article that presents t-SNE. Published 11/2008
https://jmlr.org/papers/volume9/vandermaaten08a/vandermaaten08a.pdf
T-distributed stochastic neighbor embedding (t-SNE) is a statistical method for visualizing high-dimensional data in 2 or 3 dimensions.
#DataVisualization #tSNE #MachineLearning #DimensionalityReduction #DataScience #AI #DataAnalysis #DataAnalytics

Differences in visualizing high-dimensional data with #UMAP, #tSNE and #PCA using the Collection Space Navigator
https://collection-space-navigator.github.io/
#CollectionSpaceNavigator #DataVisualization #MultidimensionalData #DimensionalityReduction #MachineLearning #OpenSource #ResearchTool @schichmax @mcanet @andreskarjus @tillmannohm

Differences in visualizing high-dimensional data with #UMAP, #tSNE and #PCA using the Collection Space Navigator
https://collection-space-navigator.github.io/
#CollectionSpaceNavigator #DataVisualization #MultidimensionalData #DimensionalityReduction #MachineLearning #OpenSource #ResearchTool @schichmax @mcanet @andreskarjus @tillmannohm

“Regardless of how we do dimensionality reduction, if the assumptions and biases underlying a method are not understood then it can be possible to see things in the data that aren’t there. “

#PCA #DimensionalityReduction #statistics

https://doi.org/10.1073/pnas.2319169120

Why the simplest explanation isn’t always the best: #DimensionalityReduction such as #PCA can see structures that do not exist and miss structures that exist. The simplest explanation isn’t always the best.

✍️ Dyer & Kording ( @kordinglab) (2023)
🌍 https://www.pnas.org/doi/10.1073/pnas.2319169120

#DataAnalysis #CompNeuro

Why the simplest explanation isn’t always the best: #DimensionalityReduction such as #PCA can see structures that do not exist and miss structures that exist. The simplest explanation isn’t always the best.

✍️ Dyer & Kording ( @kordinglab) (2023)
🌍 https://www.pnas.org/doi/10.1073/pnas.2319169120

#DataAnalysis #CompNeuro

🌌🔬 BEP39: the Dimensionality Reduction-Based Networks proposal (https://docs.google.com/document/d/1GTWsj0MFQedXjOaNk6H0or6IDVFyMAysrJ9I4Zmpz2E/edit?usp=sharing)! Capture high-dimensional brain data complexity and explore their lower-dimensional representation with BIDS. #BrainDataAnalysis #DimensionalityReduction

🌌🔬 BEP39: the Dimensionality Reduction-Based Networks proposal (https://docs.google.com/document/d/1GTWsj0MFQedXjOaNk6H0or6IDVFyMAysrJ9I4Zmpz2E/edit?usp=sharing)! Capture high-dimensional brain data complexity and explore their lower-dimensional representation with BIDS. #BrainDataAnalysis #DimensionalityReduction

Ahh I've been so excited for this paper to come out for ages!! No affiliation, just think it's super cool:

"Collection Space Navigator" for exploring projections of visual art collections

Honestly, when I first saw this, it wasn't the art applications that intrigued me so much as the value it offers for understanding 'slices' through high-dimensional space.

Demo: https://collection-space-navigator.github.io/CSN/

Website: https://collection-space-navigator.github.io/

#machinelearning #dimensionalityreduction #arts #datavisualization

Ahh I've been so excited for this paper to come out for ages!! No affiliation, just think it's super cool:

"Collection Space Navigator" for exploring projections of visual art collections

Honestly, when I first saw this, it wasn't the art applications that intrigued me so much as the value it offers for understanding 'slices' through high-dimensional space.

Demo: https://collection-space-navigator.github.io/CSN/

Website: https://collection-space-navigator.github.io/

#machinelearning #dimensionalityreduction #arts #datavisualization

from the standpoint of model selection, parsimony often boils down to dimensionality reduction

#modelSelection #parsimony #OccamsRazor #dimensionalityReduction #degreesOfFreedom #complexity #informationTheory #biasVarianceTradeoff #overfitting #underfitting #optimization #parameterTuning #crossValidation #inverseProblems #inference #statisticalLearning #machineLearning #ML #dataScience #modeling #decisionTheory #fitting #regression #classification #residualError #costFunction #performanceLoss

from the standpoint of model selection, parsimony often boils down to dimensionality reduction

#modelSelection #parsimony #OccamsRazor #dimensionalityReduction #degreesOfFreedom #complexity #informationTheory #biasVarianceTradeoff #overfitting #underfitting #optimization #parameterTuning #crossValidation #inverseProblems #inference #statisticalLearning #machineLearning #ML #dataScience #modeling #decisionTheory #fitting #regression #classification #residualError #costFunction #performanceLoss

`It is considered a non-linear approach as the mapping cannot be represented as a linear combination of the original variables as possible in techniques such as principal component analysis, which also makes it more difficult to use for classification applications`

https://en.wikipedia.org/wiki/Sammon_mapping

#machineLearning #clustering #classification #featureExtraction #featureEngineering #featureSelection #featureRanking #dimensionalityReduction #nonlinear

A spectral method for assessing and combining multiple data visualizations https://www.nature.com/articles/s41467-023-36492-2.epdf Code: https://github.com/rongstat/meta-visualization #dataviz #datascience #python #matplotlib #dimensionalityreduction

A spectral method for assessing and combining multiple data visualizations https://www.nature.com/articles/s41467-023-36492-2.epdf Code: https://github.com/rongstat/meta-visualization #dataviz #datascience #python #matplotlib #dimensionalityreduction

#arxivfeed :

"Get a new perspective on EEG: Convolutional neural network encoders for parametric t-SNE."
https://www.biorxiv.org/content/10.1101/2022.12.08.519691v1

#Neuroscience #Neuro #Brain #Neuroimaging #EEG #DimensionalityReduction #tSNE #DeepLearning #NeuralNetworks

Alright, that's all for today's #quiz. As "usual" (OK, this is new here, but usual for Twitter I guess), answers and discussion in 2-3 days; in the meantime, please ask questions, or post comments below!

#dimensionalityreduction

8/end

@mathieualain research on #RL here.

Also:
#AI4Science #causalinference
#manifoldlearning #dimensionalityreduction
#computationalsustainability
#forestwildfire