Dimensionality Reduction

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

2 leaderboard tables shown for this task, 2 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.

Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

11 datasets whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

2 subtasks in the archive's task tree.

Most implemented papers archive 2025-07-28

30 shown of 857 papers with code (3,304 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction
  9 Feb 2018 39 repositories listed
  UMAP (Uniform Manifold Approximation and Projection) is a novel manifold learning technique for dimension reduction.
• Adversarial Autoencoders
  18 Nov 2015 29 repositories listed Syntology ran 8 of 12 samples · 4 unverified · 9 pointer-only (licence)
  In this paper, we propose the "adversarial autoencoder" (AAE), which is a probabilistic autoencoder that uses the recently proposed generative adversarial networks (GAN) to perform variational inference by matching the…
• XGBoost: A Scalable Tree Boosting System
  9 Mar 2016 28 repositories listed Syntology ran 0 of 17 samples · 17 unverified
  In this paper, we describe a scalable end-to-end tree boosting system called XGBoost, which is used widely by data scientists to achieve state-of-the-art results on many machine learning challenges.
• ECA-Net: Efficient Channel Attention for Deep Convolutional Neural Networks
  8 Oct 2019 13 repositories listed Syntology ran 1 of 8 samples · 7 unverified
  By dissecting the channel attention module in SENet, we empirically show avoiding dimensionality reduction is important for learning channel attention, and appropriate cross-channel interaction can preserve performance…
• Rethinking Spatial Dimensions of Vision Transformers
  30 Mar 2021 12 repositories listed Syntology ran 10 of 20 samples · 10 unverified
  We empirically show that such a spatial dimension reduction is beneficial to a transformer architecture as well, and propose a novel Pooling-based Vision Transformer (PiT) upon the original ViT model.
• Towards K-means-friendly Spaces: Simultaneous Deep Learning and Clustering
  15 Oct 2016 11 repositories listed Syntology ran 3 of 3 samples · 0 unverified · 1 pointer-only (licence)
  To recover the `clustering-friendly' latent representations and to better cluster the data, we propose a joint DR and K-means clustering approach in which DR is accomplished via learning a deep neural network (DNN).
• CatBoost: unbiased boosting with categorical features
  28 Jun 2017 10 repositories listed
  This paper presents the key algorithmic techniques behind CatBoost, a new gradient boosting toolkit.
• Efficient Algorithms for t-distributed Stochastic Neighborhood Embedding
  25 Dec 2017 8 repositories listed Syntology ran 0 of 6 samples · 6 unverified · 1 pointer-only (licence)
  t-distributed Stochastic Neighborhood Embedding (t-SNE) is a method for dimensionality reduction and visualization that has become widely popular in recent years.
• SOM-VAE: Interpretable Discrete Representation Learning on Time Series
  6 Jun 2018 6 repositories listed Syntology ran 0 of 6 samples · 6 unverified
  We evaluate our model in terms of clustering performance and interpretability on static (Fashion-)MNIST data, a time series of linearly interpolated (Fashion-)MNIST images, a chaotic Lorenz attractor system with two…
• Unifying Deep Local and Global Features for Image Search
  14 Jan 2020 5 repositories listed
  Image retrieval is the problem of searching an image database for items that are similar to a query image.
• Unsupervised speech representation learning using WaveNet autoencoders
  25 Jan 2019 5 repositories listed
  We consider the task of unsupervised extraction of meaningful latent representations of speech by applying autoencoding neural networks to speech waveforms.
• ZOO: Zeroth Order Optimization based Black-box Attacks to Deep Neural Networks without Training Substitute Models
  14 Aug 2017 5 repositories listed Syntology ran 1 of 1 samples · 0 unverified
  However, different from leveraging attack transferability from substitute models, we propose zeroth order optimization (ZOO) based attacks to directly estimate the gradients of the targeted DNN for generating…
• Diagnosing and Fixing Manifold Overfitting in Deep Generative Models
  14 Apr 2022 4 repositories listed
  We propose a class of two-step procedures consisting of a dimensionality reduction step followed by maximum-likelihood density estimation, and prove that they recover the data-generating distribution in the…
• The Signature Kernel is the solution of a Goursat PDE
  26 Jun 2020 4 repositories listed Syntology ran 1 of 10 samples · 9 unverified
  Recently, there has been an increased interest in the development of kernel methods for learning with sequential data.
• GP-VAE: Deep Probabilistic Time Series Imputation
  9 Jul 2019 4 repositories listed Syntology ran 0 of 12 samples · 12 unverified
  Multivariate time series with missing values are common in areas such as healthcare and finance, and have grown in number and complexity over the years.
• Adapting Text Embeddings for Causal Inference
  29 May 2019 4 repositories listed
  To address this challenge, we develop causally sufficient embeddings, low-dimensional document representations that preserve sufficient information for causal identification and allow for efficient estimation of causal…
• Deep Temporal Clustering : Fully Unsupervised Learning of Time-Domain Features
  4 Feb 2018 4 repositories listed
  Here we propose a novel algorithm, Deep Temporal Clustering (DTC), to naturally integrate dimensionality reduction and temporal clustering into a single end-to-end learning framework, fully unsupervised.
• TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems
  14 Mar 2016 4 repositories listed
  TensorFlow is an interface for expressing machine learning algorithms, and an implementation for executing such algorithms.
• A Primer on the Signature Method in Machine Learning
  11 Mar 2016 4 repositories listed Syntology ran 4 of 6 samples · 2 unverified · 3 pointer-only (licence)
  The signature is a sequence of numbers associated with a path that captures many of its important analytic and geometric properties.
• FiLM: Frequency improved Legendre Memory Model for Long-term Time Series Forecasting
  18 May 2022 3 repositories listed Syntology ran 17 of 18 samples · 1 unverified
  Recent studies have shown that deep learning models such as RNNs and Transformers have brought significant performance gains for long-term forecasting of time series because they effectively utilize historical…
• Wassmap: Wasserstein Isometric Mapping for Image Manifold Learning
  13 Apr 2022 3 repositories listed
  In this paper, we propose Wasserstein Isometric Mapping (Wassmap), a nonlinear dimensionality reduction technique that provides solutions to some drawbacks in existing global nonlinear dimensionality reduction…
• M-ar-K-Fast Independent Component Analysis
  17 Aug 2021 3 repositories listed
  This study presents the m-arcsinh Kernel ('m-ar-K') Fast Independent Component Analysis ('FastICA') method ('m-ar-K-FastICA') for feature extraction.
• Improving the HardNet Descriptor
  19 Jul 2020 3 repositories listed
  In the thesis we consider the problem of local feature descriptor learning for wide baseline stereo focusing on the HardNet descriptor, which is close to state-of-the-art.
• Extracting the main trend in a dataset: the Sequencer algorithm
  24 Jun 2020 3 repositories listed
  However, some are challenging to detect as they may be expressed in complex manners.
• Semantic Relatedness Based Re-ranker for Text Spotting
  17 Sep 2019 3 repositories listed
  We present a scenario where semantic similarity is not enough, and we devise a neural approach to learn semantic relatedness.
• catch22: CAnonical Time-series CHaracteristics
  29 Jan 2019 3 repositories listed
  Capturing the dynamical properties of time series concisely as interpretable feature vectors can enable efficient clustering and classification for time-series applications across science and industry.
• CatBoost: gradient boosting with categorical features support
  24 Oct 2018 3 repositories listed Syntology ran 0 of 7 samples · 7 unverified
  In this paper we present CatBoost, a new open-sourced gradient boosting library that successfully handles categorical features and outperforms existing publicly available implementations of gradient boosting in terms of…
• Unsupervised Metric Learning in Presence of Missing Data
  19 Jul 2018 3 repositories listed
  Here, we present a new algorithm MR-MISSING that extends these previous algorithms and can be used to compute low dimensional representation on data sets with missing entries.
• Reservoir computing approaches for representation and classification of multivariate time series
  21 Mar 2018 3 repositories listed Syntology ran 0 of 5 samples · 5 unverified
  The architectures are compared to other MTS classifiers, including deep learning models and time series kernels.
• Deep Continuous Clustering
  5 Mar 2018 3 repositories listed
  We present a clustering algorithm that performs nonlinear dimensionality reduction and clustering jointly.

Syntology lines on 14 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.