SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

Showing 150 of 3304 papers

TitleStatusHype
Revisiting PCA for time series reduction in temporal dimensionCode7
Dimension Reduction with Locally Adjusted GraphsCode4
XGBoost: A Scalable Tree Boosting SystemCode4
Parametric UMAP embeddings for representation and semi-supervised learningCode3
ivis Dimensionality Reduction Framework for Biomacromolecular SimulationsCode3
Learning 3D Human Pose Estimation from Dozens of Datasets using a Geometry-Aware Autoencoder to Bridge Between Skeleton FormatsCode2
Modular Boundaries in Recurrent Neural NetworksCode2
Efficient Multi-Scale Attention Module with Cross-Spatial LearningCode2
LeanVec: Searching vectors faster by making them fitCode2
RetroMAE v2: Duplex Masked Auto-Encoder For Pre-Training Retrieval-Oriented Language ModelsCode2
TTS-GAN: A Transformer-based Time-Series Generative Adversarial NetworkCode2
A Survey on Generative Diffusion ModelCode2
Discover and Mitigate Multiple Biased Subgroups in Image ClassifiersCode2
ECA-Net: Efficient Channel Attention for Deep Convolutional Neural NetworksCode2
High-dimensional mixed-categorical Gaussian processes with application to multidisciplinary design optimization for a green aircraftCode2
Geomstats: A Python Package for Riemannian Geometry in Machine LearningCode2
ImMesh: An Immediate LiDAR Localization and Meshing FrameworkCode2
Nes2Net: A Lightweight Nested Architecture for Foundation Model Driven Speech Anti-spoofingCode2
ProtTrans: Towards Cracking the Language of Life's Code Through Self-Supervised Deep Learning and High Performance ComputingCode2
Deep Learning for Functional Data Analysis with Adaptive Basis LayersCode1
Deep Convolutional Autoencoders for reconstructing magnetic resonance images of the healthy brainCode1
Deep Learning for Reduced Order Modelling and Efficient Temporal Evolution of Fluid SimulationsCode1
Aha! Adaptive History-Driven Attack for Decision-Based Black-Box ModelsCode1
DartMinHash: Fast Sketching for Weighted SetsCode1
Correlation-based feature selection to identify functional dynamics in proteinsCode1
Curvature-based Feature Selection with Application in Classifying Electronic Health RecordsCode1
A Hybrid Architecture for Out of Domain Intent Detection and Intent DiscoveryCode1
Deep active subspaces - a scalable method for high-dimensional uncertainty propagationCode1
Deep Dimension Reduction for Supervised Representation LearningCode1
Deep Domain Adaptation: A Sim2Real Neural Approach for Improving Eye-Tracking SystemsCode1
The Signature Kernel is the solution of a Goursat PDECode1
Effective Sample Size, Dimensionality, and Generalization in Covariate Shift AdaptationCode1
DataLens: Scalable Privacy Preserving Training via Gradient Compression and AggregationCode1
Deep reconstruction of strange attractors from time seriesCode1
Binary Bleed: Fast Distributed and Parallel Method for Automatic Model SelectionCode1
BayesOpt Adversarial AttackCode1
CatBoost: gradient boosting with categorical features supportCode1
Algorithmic Stability and Generalization of an Unsupervised Feature Selection AlgorithmCode1
Automatic Recognition of Abdominal Organs in Ultrasound Images based on Deep Neural Networks and K-Nearest-Neighbor ClassificationCode1
AUCO ResNet: an end-to-end network for Covid-19 pre-screening from cough and breathCode1
ActUp: Analyzing and Consolidating tSNE and UMAPCode1
Autoencoding with a Classifier SystemCode1
BasisVAE: Translation-invariant feature-level clustering with Variational AutoencodersCode1
Bayesian Optimization of Sampling Densities in MRICode1
Adversarial AutoencodersCode1
BIKED: A Dataset for Computational Bicycle Design with Machine Learning BenchmarksCode1
Clustering with UMAP: Why and How Connectivity MattersCode1
Collection Space Navigator: An Interactive Visualization Interface for Multidimensional DatasetsCode1
Scalable conditional deep inverse Rosenblatt transports using tensor-trains and gradient-based dimension reductionCode1
ATD: Augmenting CP Tensor Decomposition by Self SupervisionCode1
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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