Stochastic Neighbor

Stochastic neighbor methods aim to represent high-dimensional data in lower dimensions while preserving the relationships between data points, primarily focusing on neighborhood structures. Current research emphasizes improvements to existing algorithms like t-SNE and UMAP, incorporating uncertainty awareness, hierarchical structures, and adaptive neighbor selection to enhance visualization accuracy and efficiency across diverse applications such as single-cell RNA sequencing, video annotation, and image recognition. These advancements are significant for improving data analysis and visualization in various fields, enabling more effective exploration and interpretation of complex datasets.

Papers

November 15, 2024

Attraction-Repulsion Swarming: A Generalized Framework of t-SNE via Force Normalization and Tunable Interactions
Jingcheng Lu, Jeff Calder
Visualization Tool Force Estimation Generalized Framework SNE Algorithm Stochastic Neighbor Visualization Method

October 1, 2024

Uncertainty-aware t-distributed Stochastic Neighbor Embedding for Single-cell RNA-seq Data
Hui Ma, Kai Chen
Uncertainty Aware Single Cell Single Cell RNA Gene Expression SNE Algorithm Stochastic Neighbor Uncertainty Visualization

September 16, 2024

HAVANA: Hierarchical stochastic neighbor embedding for Accelerated Video ANnotAtions
Alexandru Bobe, Jan C. van Gemert
Large Scale Video Video Annotation Stochastic Neighbor Stochastic Neighbor Embedding

August 6, 2024

Doubly Stochastic Adaptive Neighbors Clustering via the Marcus Mapping
Jinghui Yuan, Chusheng Zeng, Fangyuan Xie, Zhe Cao, Mulin Chen, Rong Wang, Feiping Nie, Yuan Yuan
Stochastic Neighbor Graph Based Clustering Adaptive Clustering Stochastic Matrix High Fidelity Mapping

July 14, 2024

SpreadFGL: Edge-Client Collaborative Federated Graph Learning with Adaptive Neighbor Generation
Luying Zhong, Yueyang Pi, Zheyi Chen, Zhengxin Yu, Wang Miao, Xing Chen, Geyong Min
Federated Graph Learning Graph Datasets Stochastic Neighbor Graph Imputation

December 1, 2023

Quantum Kernel t-Distributed Stochastic Neighbor Embedding
Yoshiaki Kawase, Kosuke Mitarai, Keisuke Fujii
Quantum Machine Learning Quantum Circuit Quantum Kernel Stochastic Neighbor Visualization Method

September 15, 2023

Supervised Stochastic Neighbor Embedding Using Contrastive Learning
Yi Zhang
Contrastive Learning Dimensionality Reduction Self Supervised Contrastive Learning Contrastive Method Fully Supervised Stochastic Neighbor

August 29, 2023

Tuning the perplexity for and computing sampling-based t-SNE embeddings
Martin Skrodzki, Nicolas Chaves-de-Plaza, Klaus Hildebrandt, Thomas Höllt, Elmar Eisemann
Jina Embeddings High Dimensional Data SNE Algorithm Stochastic Neighbor Dimensional Visualization

August 14, 2023

pNNCLR: Stochastic Pseudo Neighborhoods for Contrastive Learning based Unsupervised Representation Learning Problems
Momojit Biswas, Himanshu Buckchash, Dilip K. Prasad
Contrastive Learning Self Supervised Learning Nearest Neighbor Medical Image Datasets Unsupervised Visual Representation Learning Stochastic Neighbor

July 13, 2023

Kernel t-distributed stochastic neighbor embedding
Denis C. Ilie-Ablachim, Bogdan Dumitrescu, Cristian Rusu
High Dimensional Data Kernel Method Kernel Extension Pairwise Distance Dimensional Space SNE Algorithm Stochastic Neighbor

February 7, 2023

Using t-distributed stochastic neighbor embedding for visualization and segmentation of 3D point clouds of plants
Helin Dutagaci
3D Point Cloud Interactive Visualization Plant Monitoring Plant Identification Stochastic Neighbor

December 22, 2022

A machine learning framework for neighbor generation in metaheuristic search
Defeng Liu, Vincent Perreault, Alain Hertz, Andrea Lodi
Combinatorial Optimization Problem Metaheuristic Algorithm Machine Learning Framework Metaheuristic Approach Stochastic Neighbor Neighborhood Search

November 16, 2022

Informative Initialization and Kernel Selection Improves t-SNE for Biological Sequences
Prakash Chourasia, Sarwan Ali, Murray Patterson
Biological Sequence Gaussian Kernel SNE Algorithm Stochastic Neighbor Kernel Selection

May 30, 2022

Your Contrastive Learning Is Secretly Doing Stochastic Neighbor Embedding
Tianyang Hu, Zhili Liu, Fengwei Zhou, Wenjia Wang, Weiran Huang
Contrastive Learning Self Supervised Contrastive Learning Pairwise Similarity Stochastic Neighbor Domain Specific Augmentation

May 24, 2022

ENS-t-SNE: Embedding Neighborhoods Simultaneously t-SNE
Jacob Miller, Vahan Huroyan, Raymundo Navarrete, Md Iqbal Hossain, Stephen Kobourov
High Dimensional Dimension Reduction Dimensional Embeddings Neighborhood Level SNE Algorithm Stochastic Neighbor

March 17, 2022

Visualizing Riemannian data with Rie-SNE
Andri Bergsson, Søren Hauberg
Riemannian Manifold Riemannian Geometry Approach Stochastic Neighbor Riemannian Diffusion

February 9, 2022

Parametric t-Stochastic Neighbor Embedding With Quantum Neural Network
Yoshiaki Kawase, Kosuke Mitarai, Keisuke Fujii
Quantum Machine Learning Quantum Neural Network SNE Algorithm Stochastic Neighbor Stochastic Neighbor Embedding Quantum Datasets

February 8, 2022

Ada-NETS: Face Clustering via Adaptive Neighbour Discovery in the Structure Space
Yaohua Wang, Yaobin Zhang, Fangyi Zhang, Ming Lin, YuQi Zhang, Senzhang Wang, Xiuyu Sun
Time Series Stochastic Neighbor Face Interaction Graph Network Face Clustering