SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

Showing 51100 of 3304 papers

TitleStatusHype
A preprocessing perspective for quantum machine learning classification advantage using NISQ algorithmsCode1
Application of Clustering Algorithms for Dimensionality Reduction in Infrastructure Resilience Prediction ModelsCode1
Fast Network Embedding Enhancement via High Order Proximity ApproximationCode1
Approximating Likelihood Ratios with Calibrated Discriminative ClassifiersCode1
Deep Learning for Reduced Order Modelling and Efficient Temporal Evolution of Fluid SimulationsCode1
FiLM: Frequency improved Legendre Memory Model for Long-term Time Series ForecastingCode1
On Path Integration of Grid Cells: Group Representation and Isotropic ScalingCode1
Flows for simultaneous manifold learning and density estimationCode1
A Spectral Method for Assessing and Combining Multiple Data VisualizationsCode1
DefakeHop: A Light-Weight High-Performance Deepfake DetectorCode1
Dimension Reduction for Efficient Dense Retrieval via Conditional AutoencoderCode1
Generative locally linear embedding: A module for manifold unfolding and visualizationCode1
Deep active subspaces - a scalable method for high-dimensional uncertainty propagationCode1
Curvature-based Feature Selection with Application in Classifying Electronic Health RecordsCode1
Deep Convolutional Autoencoders for reconstructing magnetic resonance images of the healthy brainCode1
The Signature Kernel is the solution of a Goursat PDECode1
Aha! Adaptive History-Driven Attack for Decision-Based Black-Box ModelsCode1
Clustering with UMAP: Why and How Connectivity MattersCode1
Scalable conditional deep inverse Rosenblatt transports using tensor-trains and gradient-based dimension reductionCode1
Deep Dimension Reduction for Supervised Representation LearningCode1
BIKED: A Dataset for Computational Bicycle Design with Machine Learning BenchmarksCode1
CBMAP: Clustering-based manifold approximation and projection for dimensionality reductionCode1
A hyperparameter-tuning approach to automated inverse planningCode1
Collection Space Navigator: An Interactive Visualization Interface for Multidimensional DatasetsCode1
Correlation-based feature selection to identify functional dynamics in proteinsCode1
Effective Sample Size, Dimensionality, and Generalization in Covariate Shift AdaptationCode1
DartMinHash: Fast Sketching for Weighted SetsCode1
DataLens: Scalable Privacy Preserving Training via Gradient Compression and AggregationCode1
Adversarial AutoencodersCode1
A Hybrid Architecture for Out of Domain Intent Detection and Intent DiscoveryCode1
Deep reconstruction of strange attractors from time seriesCode1
Deep Learning of Individual AestheticsCode1
Derivative-Informed Neural Operator: An Efficient Framework for High-Dimensional Parametric Derivative LearningCode1
Detection and Retrieval of Out-of-Distribution Objects in Semantic SegmentationCode1
A local approach to parameter space reduction for regression and classification tasksCode1
DIAS: A Dataset and Benchmark for Intracranial Artery Segmentation in DSA sequencesCode1
Binary Bleed: Fast Distributed and Parallel Method for Automatic Model SelectionCode1
Bayesian Optimization of Sampling Densities in MRICode1
A Memory Efficient Baseline for Open Domain Question AnsweringCode1
ActUp: Analyzing and Consolidating tSNE and UMAPCode1
DistilProtBert: A distilled protein language model used to distinguish between real proteins and their randomly shuffled counterpartsCode1
Distributed Out-of-Memory NMF on CPU/GPU ArchitecturesCode1
An Additive Autoencoder for Dimension EstimationCode1
DMCNet: Diversified Model Combination Network for Understanding Engagement from Video ScreengrabsCode1
BasisVAE: Translation-invariant feature-level clustering with Variational AutoencodersCode1
A New Basis for Sparse Principal Component AnalysisCode1
An Embedding is Worth a Thousand Noisy LabelsCode1
Enhanced MRI brain tumor detection and classification via topological data analysis and low-rank tensor decompositionCode1
Towards a More Rigorous Science of Blindspot Discovery in Image Classification ModelsCode1
BayesOpt Adversarial AttackCode1
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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