SOTAVerified

Dimensionality Reduction

Dimensionality reduction is the task of reducing the dimensionality of a dataset.

( Image credit: openTSNE )

Papers

Showing 31113120 of 3304 papers

TitleStatusHype
Lens functions for exploring UMAP Projections with Domain KnowledgeCode0
Online Detection of Sparse Changes in High-Dimensional Data Streams Using Tailored ProjectionsCode0
Calibrating dimension reduction hyperparameters in the presence of noiseCode0
Data Mapping and Finite Difference LearningCode0
From deep learning to mechanistic understanding in neuroscience: the structure of retinal predictionCode0
From Gameplay to Symbolic Reasoning: Learning SAT Solver Heuristics in the Style of Alpha(Go) ZeroCode0
From Images to Features: Unbiased Morphology Classification via Variational Auto-Encoders and Domain AdaptationCode0
LEt-SNE: A Hybrid Approach To Data Embedding and Visualization of Hyperspectral ImageryCode0
Let There Be Order: Rethinking Ordering in Autoregressive Graph GenerationCode0
A journey in ESN and LSTM visualisations on a language taskCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1UDRNClassification Accuracy90.9Unverified
2tSNEClassification Accuracy51.5Unverified
3IVISClassification Accuracy46.6Unverified
4UMAPClassification Accuracy41.3Unverified
#ModelMetricClaimedVerifiedStatus
1UDRNClassification Accuracy71.1Unverified
2QSClassification Accuracy68Unverified