Clustering

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

No benchmark for this task in the archive.

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

5 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 2,823 papers with code (10,718 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.

• FaceNet: A Unified Embedding for Face Recognition and Clustering
  12 Mar 2015 183 repositories listed Syntology ran 65 of 154 samples · 89 unverified · 45 pointer-only (licence)
  On the widely used Labeled Faces in the Wild (LFW) dataset, our system achieves a new record accuracy of 99.
• Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks
  27 Aug 2019 64 repositories listed Syntology ran 20 of 58 samples · 38 unverified · 11 pointer-only (licence)
  However, it requires that both sentences are fed into the network, which causes a massive computational overhead: Finding the most similar pair in a collection of 10, 000 sentences requires about 50 million inference…
• 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.
• SOLO: Segmenting Objects by Locations
  10 Dec 2019 24 repositories listed
  We present a new, embarrassingly simple approach to instance segmentation in images.
• Unsupervised Deep Embedding for Clustering Analysis
  19 Nov 2015 23 repositories listed Syntology ran 2 of 25 samples · 23 unverified · 3 pointer-only (licence)
  Clustering is central to many data-driven application domains and has been studied extensively in terms of distance functions and grouping algorithms.
• Deep Speaker: an End-to-End Neural Speaker Embedding System
  5 May 2017 15 repositories listed Syntology ran 7 of 9 samples · 2 unverified · 5 pointer-only (licence)
  We present Deep Speaker, a neural speaker embedding system that maps utterances to a hypersphere where speaker similarity is measured by cosine similarity.
• HuBERT: Self-Supervised Speech Representation Learning by Masked Prediction of Hidden Units
  14 Jun 2021 11 repositories listed Syntology ran 0 of 9 samples · 9 unverified
  Self-supervised approaches for speech representation learning are challenged by three unique problems: (1) there are multiple sound units in each input utterance, (2) there is no lexicon of input sound units during the…
• Variational Deep Embedding: An Unsupervised and Generative Approach to Clustering
  16 Nov 2016 11 repositories listed Syntology ran 1 of 3 samples · 2 unverified · 2 pointer-only (licence)
  In this paper, we propose Variational Deep Embedding (VaDE), a novel unsupervised generative clustering approach within the framework of Variational Auto-Encoder (VAE).
• 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).
• Key Points Estimation and Point Instance Segmentation Approach for Lane Detection
  16 Feb 2020 10 repositories listed Syntology ran 1 of 8 samples · 7 unverified
  In the case of traffic line detection, an essential perception module, many condition should be considered, such as number of traffic lines and computing power of the target system.
• 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.
• Deep Clustering for Unsupervised Learning of Visual Features
  15 Jul 2018 9 repositories listed Syntology ran 5 of 7 samples · 2 unverified · 4 pointer-only (licence)
  In this work, we present DeepCluster, a clustering method that jointly learns the parameters of a neural network and the cluster assignments of the resulting features.
• Leveraging BERT for Extractive Text Summarization on Lectures
  7 Jun 2019 8 repositories listed
  This paper reports on the project called Lecture Summarization Service, a python based RESTful service that utilizes the BERT model for text embeddings and KMeans clustering to identify sentences closes to the centroid…
• Entity Embeddings of Categorical Variables
  22 Apr 2016 8 repositories listed Syntology ran 2 of 2 samples · 0 unverified · 2 pointer-only (licence)
  As entity embedding defines a distance measure for categorical variables it can be used for visualizing categorical data and for data clustering.
• Deep clustering: Discriminative embeddings for segmentation and separation
  18 Aug 2015 8 repositories listed Syntology ran 2 of 3 samples · 1 unverified · 3 pointer-only (licence)
  The framework can be used without class labels, and therefore has the potential to be trained on a diverse set of sound types, and to generalize to novel sources.
• DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition
  6 Oct 2013 8 repositories listed Syntology ran 1 of 7 samples · 6 unverified · 1 pointer-only (licence)
  We evaluate whether features extracted from the activation of a deep convolutional network trained in a fully supervised fashion on a large, fixed set of object recognition tasks can be re-purposed to novel generic…
• ClusterGAN : Latent Space Clustering in Generative Adversarial Networks
  10 Sep 2018 7 repositories listed Syntology ran 0 of 5 samples · 5 unverified
  While one can potentially exploit the latent-space back-projection in GANs to cluster, we demonstrate that the cluster structure is not retained in the GAN latent space.
• A high-bias, low-variance introduction to Machine Learning for physicists
  23 Mar 2018 7 repositories listed Syntology ran 2 of 14 samples · 12 unverified
  The purpose of this review is to provide an introduction to the core concepts and tools of machine learning in a manner easily understood and intuitive to physicists.
• Enhancing Geometric Factors in Model Learning and Inference for Object Detection and Instance Segmentation
  7 May 2020 6 repositories listed Syntology ran 2 of 5 samples · 3 unverified · 5 pointer-only (licence)
  In this paper, we propose Complete-IoU (CIoU) loss and Cluster-NMS for enhancing geometric factors in both bounding box regression and Non-Maximum Suppression (NMS), leading to notable gains of average precision (AP)…
• Agglomerative Likelihood Clustering
  2 Aug 2019 6 repositories listed
  We consider the problem of fast time-series data clustering.
• Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks
  20 May 2019 6 repositories listed
  Furthermore, Cluster-GCN allows us to train much deeper GCN without much time and memory overhead, which leads to improved prediction accuracy---using a 5-layer Cluster-GCN, we achieve state-of-the-art test F1 score 99.
• Multi-Interest Network with Dynamic Routing for Recommendation at Tmall
  17 Apr 2019 6 repositories listed Syntology ran 0 of 3 samples · 3 unverified
  Industrial recommender systems usually consist of the matching stage and the ranking stage, in order to handle the billion-scale of users and items.
• Invariant Information Clustering for Unsupervised Image Classification and Segmentation
  17 Jul 2018 6 repositories listed Syntology ran 2 of 18 samples · 16 unverified
  The method is not specialised to computer vision and operates on any paired dataset samples; in our experiments we use random transforms to obtain a pair from each image.
• 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…
• graph2vec: Learning Distributed Representations of Graphs
  17 Jul 2017 6 repositories listed Syntology ran 2 of 2 samples · 0 unverified · 2 pointer-only (licence)
  Recent works on representation learning for graph structured data predominantly focus on learning distributed representations of graph substructures such as nodes and subgraphs.
• Sampling Matters in Deep Embedding Learning
  23 Jun 2017 6 repositories listed Syntology ran 2 of 2 samples · 0 unverified
  In addition, we show that a simple margin based loss is sufficient to outperform all other loss functions.
• QCD-Aware Recursive Neural Networks for Jet Physics
  2 Feb 2017 6 repositories listed Syntology ran 0 of 15 samples · 15 unverified
  Recent progress in applying machine learning for jet physics has been built upon an analogy between calorimeters and images.
• PyPOTS: A Python Toolbox for Data Mining on Partially-Observed Time Series
  30 May 2023 5 repositories listed Syntology ran 0 of 21 samples · 21 unverified
  PyPOTS is an open-source Python library dedicated to data mining and analysis on multivariate partially-observed time series, i.
• Self-labelling via simultaneous clustering and representation learning
  13 Nov 2019 5 repositories listed Syntology ran 7 of 18 samples · 11 unverified · 3 pointer-only (licence)
  Combining clustering and representation learning is one of the most promising approaches for unsupervised learning of deep neural networks.

Syntology lines on 25 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.