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Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 51–60 of 3304 papers

Title	Date	Tasks	Status	Hype
DQ-LoRe: Dual Queries with Low Rank Approximation Re-ranking for In-Context Learning	Oct 4, 2023	Dimensionality ReductionIn-Context Learning	CodeCode Available	1
Multi-fidelity reduced-order surrogate modeling	Sep 1, 2023	Dimensionality Reduction	CodeCode Available	1
Ultra Dual-Path Compression For Joint Echo Cancellation And Noise Suppression	Aug 21, 2023	Dimensionality Reduction	CodeCode Available	1
ZADU: A Python Library for Evaluating the Reliability of Dimensionality Reduction Embeddings	Aug 1, 2023	Dimensionality Reduction	CodeCode Available	1
DIAS: A Dataset and Benchmark for Intracranial Artery Segmentation in DSA sequences	Jun 21, 2023	Dimensionality ReductionImage Segmentation	CodeCode Available	1
ActUp: Analyzing and Consolidating tSNE and UMAP	May 12, 2023	Dimensionality Reduction	CodeCode Available	1
Collection Space Navigator: An Interactive Visualization Interface for Multidimensional Datasets	May 11, 2023	Data VisualizationDimensionality Reduction	CodeCode Available	1
Uncovering the Inner Workings of STEGO for Safe Unsupervised Semantic Segmentation	Apr 14, 2023	Dimensionality ReductionSemantic Segmentation	CodeCode Available	1
SELFormer: Molecular Representation Learning via SELFIES Language Models	Apr 10, 2023	Dimensionality ReductionDrug Discovery	CodeCode Available	1
A Hybrid Architecture for Out of Domain Intent Detection and Intent Discovery	Mar 7, 2023	ClusteringDimensionality Reduction	CodeCode Available	1

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All datasets MCA EMNIST

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	UDRN	Classification Accuracy	90.9	—	Unverified
2	tSNE	Classification Accuracy	51.5	—	Unverified
3	IVIS	Classification Accuracy	46.6	—	Unverified
4	UMAP	Classification Accuracy	41.3	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	UDRN	Classification Accuracy	71.1	—	Unverified
2	QS	Classification Accuracy	68	—	Unverified