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 1976–2000 of 3304 papers

TitleStatusHype
RDA-INR: Riemannian Diffeomorphic Autoencoding via Implicit Neural Representations—0
Run-to-Run Control With Bayesian Optimization for Soft Landing of Short-Stroke Reluctance Actuators—0
RURANET++: An Unsupervised Learning Method for Diabetic Macular Edema Based on SCSE Attention Mechanisms and Dynamic Multi-Projection Head Clustering—0
SAGMAN: Stability Analysis of Graph Neural Networks on the Manifolds—0
Sample complexity and effective dimension for regression on manifolds—0
Sampling and multilevel coarsening algorithms for fast matrix approximations—0
SAP-sLDA: An Interpretable Interface for Exploring Unstructured Text—0
SAR Target Recognition Using the Multi-aspect-aware Bidirectional LSTM Recurrent Neural Networks—0
Scalable Adaptive Stochastic Optimization Using Random Projections—0
Scalable Amortized GPLVMs for Single Cell Transcriptomics Data—0
Scalable Derivative-Free Optimization for Nonlinear Least-Squares Problems—0
Scalable Differentially Private Clustering via Hierarchically Separated Trees—0
Scalable Iterative Algorithm for Robust Subspace Clustering—0
Scalable manifold learning by uniform landmark sampling and constrained locally linear embedding—0
Scalable Out-of-Sample Extension of Graph Embeddings Using Deep Neural Networks—0
Scalable physics-informed deep generative model for solving forward and inverse stochastic differential equations—0
SCALE SPACE FLOW WITH AUTOREGRESSIVE PRIORS—0
Scaling Up Bayesian Uncertainty Quantification for Inverse Problems using Deep Neural Networks—0
SCANN: Synthesis of Compact and Accurate Neural Networks—0
Schrödinger Risk Diversification Portfolio—0
scMamba: A Pre-Trained Model for Single-Nucleus RNA Sequencing Analysis in Neurodegenerative Disorders—0
Screening Rules and its Complexity for Active Set Identification—0
SDR-GAIN: A High Real-Time Occluded Pedestrian Pose Completion Method for Autonomous Driving—0
Segmentation of Cardiac Structures via Successive Subspace Learning with Saab Transform from Cine MRI—0
Segmented and Non-Segmented Stacked Denoising Autoencoder for Hyperspectral Band Reduction—0
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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