SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 2891–2900 of 3304 papers

TitleStatusHype
Causal learning with sufficient statistics: an information bottleneck approach—0
CAVIAR: Categorical-Variable Embeddings for Accurate and Robust Inference—0
Estimation and Inference in High-Dimensional Panel Data Models with Interactive Fixed Effects—0
Cell2State: Learning Cell State Representations From Barcoded Single-Cell Gene-Expression Transitions—0
Channel Charting: Locating Users within the Radio Environment using Channel State Information—0
Chasing Collective Variables using Autoencoders and biased trajectories—0
Chiron: A Robust Recommendation System with Graph Regularizer—0
Circuit design in biology and machine learning. II. Anomaly detection—0
Circular Coordinate Methods with Generalized Penalty Functions—0
CitiusNLP at SemEval-2018 Task 10: The Use of Transparent Distributional Models and Salient Contexts to Discriminate Word Attributes—0
Show:102550
← PrevPage 290 of 331Next →
All datasetsMCAEMNIST

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1UDRNClassification Accuracy90.9—Unverified
2tSNEClassification Accuracy51.5—Unverified
3IVISClassification Accuracy46.6—Unverified
4UMAPClassification Accuracy41.3—Unverified
#ModelMetricClaimedVerifiedStatus
1UDRNClassification Accuracy71.1—Unverified
2QSClassification Accuracy68—Unverified