Papers with Code 아카이브

Dimensionality Reduction

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법 전체 데이터셋

하위 태스크: 2
평가표: 2
보존된 평가 기록: 6

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

<span style="color:grey; opacity: 0.6">( Image credit: openTSNE )</span>

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/andrew-draganov/gidr-dun

공식 코드

GiDR-DUN; Gradient Dimensionality Reduction -- Differences and Unification

https://github.com/andrew-saydjari/EqWS.jl

공식 코드

Equivariant Wavelets: Fast Rotation and Translation Invariant Wavelet Scattering Transforms

https://github.com/andrewcharlesjones/pcpca

공식 코드

Probabilistic Contrastive Principal Component Analysis

https://github.com/andrewkimmm/tau-mt

공식 코드

Characterization of Phosphorylated Tau-Microtubule complex with Molecular Dynamics (MD) simulation

https://github.com/anfelopera/lineqGPR

공식 코드

High-dimensional additive Gaussian processes under monotonicity constraints

https://github.com/angeloschatzimparmpas/t-viSNE

공식 코드

t-viSNE: Interactive Assessment and Interpretation of t-SNE Projections

https://github.com/ankilab/spoken-100

공식 코드

SpokeN-100: A Cross-Lingual Benchmarking Dataset for The Classification of Spoken Numbers in Different Languages

https://github.com/anmsajedulalam/Patients-Severity-States-Classification-based-on-EHR-Data-using-Multiple-Machine-and-Deep-Learning

공식 코드

Patients' Severity States Classification based on Electronic Health Record (EHR) Data using Multiple Machine Learning and Deep Learning Approaches

https://github.com/anniegray52/graphs

공식 코드

Matrix factorisation and the interpretation of geodesic distance

https://github.com/anonsubdip/subspace_dip

공식 코드

Image Reconstruction via Deep Image Prior Subspaces

https://github.com/anonymous0519/hsod-bit

공식 코드

DMSSN: Distilled Mixed Spectral-Spatial Network for Hyperspectral Salient Object Detection

https://github.com/anthonymartin/RKDO-recursive-kl-divergence-optimization

공식 코드

Recursive KL Divergence Optimization: A Dynamic Framework for Representation Learning

https://github.com/antoinecollas/entropic_wasserstein_component_analysis

공식 코드

Entropic Wasserstein Component Analysis

https://github.com/aounon/center-smoothing

공식 코드

Center Smoothing: Certified Robustness for Networks with Structured Outputs

https://github.com/appliedtopology/gcc

공식 코드

Generalized Penalty for Circular Coordinate Representation

https://github.com/aradha/lin-rfm

공식 코드

Linear Recursive Feature Machines provably recover low-rank matrices

https://github.com/argintum/rtd-lite

공식 코드

RTD-Lite: Scalable Topological Analysis for Comparing Weighted Graphs in Learning Tasks

https://github.com/arthur-fyon/corr_2024

공식 코드

Dimensionality reduction of neuronal degeneracy reveals two interfering physiological mechanisms

https://github.com/arthurmensch/cogspaces

공식 코드

Learning Neural Representations of Human Cognition across Many fMRI Studies

https://github.com/arturjordao/IncrementalDimensionalityReduction

공식 코드

Covariance-free Partial Least Squares: An Incremental Dimensionality Reduction Method

https://github.com/askexplain/summary_sampling_via_folding

공식 코드

Encoding large information structures in linear algebra and statistical models

https://github.com/aufinal/hsbm

공식 코드

Sparse random hypergraphs: Non-backtracking spectra and community detection

https://github.com/auranic/ClinTrajan

공식 코드

Trajectories, bifurcations and pseudotime in large clinical datasets: applications to myocardial infarction and diabetes data

https://github.com/avakanski/A-Deep-Learning-Framework-for-Assessing-Physical-Rehabilitation-Exercises

공식 코드

A Deep Learning Framework for Assessing Physical Rehabilitation Exercises

https://github.com/avishaiwa/SPARCWave

공식 코드

Clustering Noisy Signals with Structured Sparsity Using Time-Frequency Representation

https://github.com/avrambardas/interpretable-unsupervised-learning

공식 코드

Local Explanation of Dimensionality Reduction

https://github.com/aywagner/DIPOLE

공식 코드

Improving Metric Dimensionality Reduction with Distributed Topology

https://github.com/bafanas/dim-reduction-with-cnn-lstm

공식 코드

Applying Dimensionality Reduction as Precursor to LSTM-CNN Models for Classifying Imagery and Motor Signals in ECoG-Based BCIs

https://github.com/basiralab/kaggle-brainnetprediction-toolbox

공식 코드

A Comparative Study of Machine Learning Methods for Predicting the Evolution of Brain Connectivity from a Baseline Timepoint

https://github.com/bcdutton/AdversarialCanonicalCorrelationAnalysis

공식 코드

Adversarial Canonical Correlation Analysis

https://github.com/bdwilliamson/sl_screening_supplementary

공식 코드

Practical considerations for variable screening in the super learner

https://github.com/bellet/HDSL

공식 코드

https://github.com/berkels/msiplib

공식 코드

A distribution-dependent Mumford-Shah model for unsupervised hyperspectral image segmentation

https://github.com/berrij/mcrps

공식 코드

Multivariate Probabilistic CRPS Learning with an Application to Day-Ahead Electricity Prices

https://github.com/bghojogh/Affective-Manifold

공식 코드

Affective Manifolds: Modeling Machine's Mind to Like, Dislike, Enjoy, Suffer, Worry, Fear, and Feel Like A Human

https://github.com/bghojogh/BUT-BUNCA-Triplet-Sampling

공식 코드

Batch-Incremental Triplet Sampling for Training Triplet Networks Using Bayesian Updating Theorem

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.