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 851–900 of 3304 papers

TitleStatusHype
Federated Multilinear Principal Component Analysis with Applications in Prognostics—0
Speeding up astrochemical reaction networks with autoencoders and neural ODEsCode0
A quantitative fusion strategy of stock picking and timing based on Particle Swarm Optimized-Back Propagation Neural Network and Multivariate Gaussian-Hidden Markov Model—0
Economic Forecasts Using Many Noises—0
k* Distribution: Evaluating the Latent Space of Deep Neural Networks using Local Neighborhood AnalysisCode0
A Robust and Efficient Boundary Point Detection Method by Measuring Local Direction Dispersion—0
A Masked Pruning Approach for Dimensionality Reduction in Communication-Efficient Federated Learning Systems—0
Interpretability Illusions in the Generalization of Simplified Models—0
Dimensionality Reduction and Dynamical Mode Recognition of Circular Arrays of Flame Oscillators Using Deep Neural Network—0
Geometric Data-Driven Dimensionality Reduction in MPC with Guarantees—0
Calibrating dimension reduction hyperparameters in the presence of noiseCode0
Analysis and mining of low-carbon and energy-saving tourism data characteristics based on machine learning algorithm—0
Relation between PLS and OLS regression in terms of the eigenvalue distribution of the regressor covariance matrix—0
A ripple in time: a discontinuity in American historyCode0
Defining Reference Sequences for Nocardia Species by Similarity and Clustering Analyses of 16S rRNA Gene Sequence Data—0
Linear normalised hash function for clustering gene sequences and identifying reference sequences from multiple sequence alignments—0
A Novel Deep Clustering Framework for Fine-Scale Parcellation of Amygdala Using dMRI Tractography—0
Detection and Identification Accuracy of PCA-Accelerated Real-Time Processing of Hyperspectral Imagery—0
Unsupervised Learning for Topological Classification of Transportation Networks—0
Bridging Classical and Quantum Machine Learning: Knowledge Transfer From Classical to Quantum Neural Networks Using Knowledge Distillation—0
Applying Dimensionality Reduction as Precursor to LSTM-CNN Models for Classifying Imagery and Motor Signals in ECoG-Based BCIsCode0
Thinking Outside the Box: Orthogonal Approach to Equalizing Protected Attributes—0
ODDR: Outlier Detection & Dimension Reduction Based Defense Against Adversarial Patches—0
Bounds on Representation-Induced Confounding Bias for Treatment Effect EstimationCode0
An Improved CNN-based Neural Network Model for Fruit Sugar Level Detection—0
Classification Methods Based on Machine Learning for the Analysis of Fetal Health Data—0
Bit Cipher -- A Simple yet Powerful Word Representation System that Integrates Efficiently with Language Models—0
Handling Overlapping Asymmetric Datasets -- A Twice Penalized P-Spline Approach—0
Utilizing VQ-VAE for End-to-End Health Indicator Generation in Predicting Rolling Bearing RUL—0
Finding Real-World Orbital Motion Laws from Data—0
From Pretext to Purpose: Batch-Adaptive Self-Supervised Learning—0
Simple but Effective Unsupervised Classification for Specified Domain Images: A Case Study on Fungi Images—0
Solving ARC visual analogies with neural embeddings and vector arithmetic: A generalized methodCode0
The optimal resolution level of a protein is an emergent property of its structure and dynamicsCode0
High Dimensional Binary Choice Model with Unknown Heteroskedasticity or Instrumental Variables—0
Inference and Interference: The Role of Clipping, Pruning and Loss Landscapes in Differentially Private Stochastic Gradient Descent—0
Cricket Player Profiling: Unraveling Strengths and Weaknesses Using Text Commentary Data—0
Differentiable VQ-VAE's for Robust White Matter Streamline EncodingsCode0
Covering Number of Real Algebraic Varieties and Beyond: Improved Bounds and Applications—0
Perfecting Liquid-State Theories with Machine Intelligence—0
Algorithms for Non-Negative Matrix Factorization on Noisy Data With Negative ValuesCode0
Manifold learning: what, how, and why—0
Computing Approximate _p Sensitivities—0
Visualizing DNA reaction trajectories with deep graph embedding approachesCode0
ViDa: Visualizing DNA hybridization trajectories with biophysics-informed deep graph embeddingsCode0
Practical considerations for variable screening in the super learnerCode0
3-Dimensional residual neural architecture search for ultrasonic defect detection—0
TailorMe: Self-Supervised Learning of an Anatomically Constrained Volumetric Human Shape Model—0
Learning Collective Behaviors from Observation—0
Language Model Training Paradigms for Clinical Feature EmbeddingsCode0
Show:102550
← PrevPage 18 of 67Next →
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