SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

Showing 1120 of 3304 papers

TitleStatusHype
Efficient Multi-Scale Attention Module with Cross-Spatial LearningCode2
ImMesh: An Immediate LiDAR Localization and Meshing FrameworkCode2
Learning 3D Human Pose Estimation from Dozens of Datasets using a Geometry-Aware Autoencoder to Bridge Between Skeleton FormatsCode2
RetroMAE v2: Duplex Masked Auto-Encoder For Pre-Training Retrieval-Oriented Language ModelsCode2
A Survey on Generative Diffusion ModelCode2
TTS-GAN: A Transformer-based Time-Series Generative Adversarial NetworkCode2
ProtTrans: Towards Cracking the Language of Life's Code Through Self-Supervised Deep Learning and High Performance ComputingCode2
Geomstats: A Python Package for Riemannian Geometry in Machine LearningCode2
ECA-Net: Efficient Channel Attention for Deep Convolutional Neural NetworksCode2
Recursive KL Divergence Optimization: A Dynamic Framework for Representation LearningCode1
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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