https://github.com/pykale/pykale
공식 코드PyKale: Knowledge-Aware Machine Learning from Multiple Sources in Python
Papers with Code 아카이브
Dimensionality Reduction
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 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/qchen95/Coupled-input-output-DR
공식 코드https://github.com/qianqianqi28/ca-pmi-word-embeddings
공식 코드A comparison of correspondence analysis with PMI-based word embedding methods
https://github.com/qiyuanpang/distributedlevp.jl
공식 코드https://github.com/qy849/de-deeponet
공식 코드https://github.com/radacha/tle
공식 코드Intrinsic Dimensionality Estimation within Tight Localities: A Theoretical and Experimental Analysis
https://github.com/radi-cho/srs21-public-data
공식 코드Transformers predicting the future. Applying attention in next-frame and time series forecasting
https://github.com/raimon-fa/palm-nmf
공식 코드Solving NMF with smoothness and sparsity constraints using PALM
https://github.com/rajeevsahay/ae-defenses
공식 코드https://github.com/rasmushenningsson/SMSSVD.jl
공식 코드https://github.com/ratschlab/GP-VAE
공식 코드https://github.com/ratschlab/SOM-VAE
공식 코드SOM-VAE: Interpretable Discrete Representation Learning on Time Series
https://github.com/rballester/ttpca
공식 코드Visualization of High-dimensional Scalar Functions Using Principal Parameterizations
https://github.com/rbordoloi/mudra
공식 코드https://github.com/rhgautier/Bayesian_dimension_reduction
공식 코드A Fully Bayesian Gradient-Free Supervised Dimension Reduction Method using Gaussian Processes
https://github.com/riddhishb/self-supervised-landmarks
공식 코드Leveraging Unsupervised Image Registration for Discovery of Landmark Shape Descriptor
https://github.com/rm4216/BayesOpt
공식 코드High-dimensional Bayesian optimization using low-dimensional feature spaces
https://github.com/rmojgani/PhysicsAwareAE
공식 코드Physics-aware registration based auto-encoder for convection dominated PDEs
https://github.com/robinvndaele/noisydistances
공식 코드https://github.com/rongstat/meta-visualization
공식 코드A Spectral Method for Assessing and Combining Multiple Data Visualizations
https://github.com/roymitz/perturbation_kernel_approximation
공식 코드https://github.com/roymitz/perturbation_out_of_sample_extension
공식 코드https://github.com/rsonthal/MRMissing.jl
공식 코드https://github.com/rtud2/Unique-Component-Analysis
공식 코드Capturing patterns of variation unique to a specific dataset
https://github.com/ruiqigao/grid-cell-path
공식 코드On Path Integration of Grid Cells: Group Representation and Isotropic Scaling
https://github.com/ryancorywright/ScalableSPCA.jl
공식 코드Solving Large-Scale Sparse PCA to Certifiable (Near) Optimality
https://github.com/ryojitanabe/ela_drframework
공식 코드https://github.com/s3-lab-iit/diffred
공식 코드https://github.com/saeedghoorchian/d-lints-rp
공식 코드Bayesian Non-stationary Linear Bandits for Large-Scale Recommender Systems
https://github.com/sambklein/funnels_repo
공식 코드Funnels: Exact maximum likelihood with dimensionality reduction
https://github.com/samirasamadi/Fair-PCA
공식 코드https://github.com/sandialabs/Bayesian-calibration-of-stochastic-agent-based-model-via-random-forest
공식 코드Bayesian calibration of stochastic agent based model via random forest
https://github.com/sanoscience/miss
공식 코드https://github.com/saranya8989/Causal_ML
공식 코드Selecting Robust Features for Machine Learning Applications using Multidata Causal Discovery
https://github.com/sashakolpakov/dire-jax
공식 코드DiRe-JAX: A JAX based Dimensionality Reduction Algorithm for Large-scale Data
https://github.com/sashakolpakov/ripple_in_time
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.