TopoAE++ adds cascade distortion loss to preserve cyclic structures and offers a fast planar persistent homology algorithm; the C++ code is on GitHub (Oct 3 2025). Read more: https://getnews.me/topological-autoencoders-improves-cycle-aware-dimensionality-reduction/ #topology #dimensionalityreduction

Researchers presented a Multi‑Scale Geometric Autoencoder that preserves global and local geometry, delivering better reconstruction and clearer clusters on Swiss‑roll and S‑curve data. https://getnews.me/multi-scale-geometric-autoencoder-improves-latent-space-structure/ #ml #dimensionalityreduction

A tensor‑based Trace Ratio framework extends LDA to higher‑order data, enabling dimensionality reduction without flattening. Submitted 18 September 2025. Read more: https://getnews.me/tensor-trace-ratio-method-boosts-multidimensional-reduction/ #tensor #dimensionalityreduction

PCA and shrinkage‑enhanced LDA reduced the 300‑dimensional job embedding, improving top‑10 accuracy in the Engineers' Salary Prediction Challenge. https://getnews.me/dimensionality-reduction-improves-word-embeddings-for-tabular-classification/ #dimensionalityreduction #tabularml

Key feature is that we model the log-correlation matrix, for which block structures are preserved.

This leads to a natural linear factor model for dynamic correlations, where additional information from realized measures are easy to incorporate.

#FactorModels #DimensionalityReduction

Poster: A #DeepLearning Approach to #DimensionalityReduction of #SpectralIndices for Scalable #EarthSystem Analysis

16 talented participants explored exciting frontiers at the intersection of neuroscience and AI. This year’s focus: dimensionality reduction and understanding high-dimensional data through dynamical systems. #DimensionalityReduction #DataScience

An excellent article on UMAP ! 🖼️ rdcu.be/d0YZT

Please keep in mind that, UMAP does not preserve global topology of the data. Thus, using UMAP embeddings as direct inputs for trajectory inference methods can lead to inaccurate results.

#scRNAseq #pseudotime #UMAP #DimensionalityReduction

Optimizing UI Element Order Doubles Performance of LM Agents in Virtual Environments 🚀💻📊 www.azoai.com/news/2024092... #AI #LanguageModels #UIOptimization #VirtualEnvironments #AgentPerformance #PixelOnly #DimensionalityReduction #ObjectDetection #TechInnovation #OmniACT @arxiv-stat-ml.bsky.social