{"total":13,"rows":[{"id":"2303.15103","title":"Contrastive Learning Is Spectral Clustering On Similarity Graph","created":"2023-03-27","cited_by_count":25,"area":null},{"id":"2305.17326","title":"Matrix Information Theory for Self-Supervised Learning","created":"2023-05-27","cited_by_count":21,"area":null},{"id":"2305.13797","title":"SNEkhorn: Dimension Reduction with Symmetric Entropic Affinities","created":"2023-05-23","cited_by_count":12,"area":null},{"id":"2402.02239","title":"Distributional Reduction: Unifying Dimensionality Reduction and Clustering with Gromov-Wasserstein","created":"2024-02-03","cited_by_count":12,"area":null},{"id":"2412.15426","title":"Dimension Reduction with Locally Adjusted Graphs","created":"2024-12-19","cited_by_count":9,"area":null},{"id":"2410.16608","title":"Assessing and improving reliability of neighbor embedding methods: a map-continuity perspective","created":"2024-10-22","cited_by_count":5,"area":null},{"id":"2403.10978","title":"Lambda: Learning Matchable Prior For Entity Alignment with Unlabeled Dangling Cases","created":"2024-03-16","cited_by_count":3,"area":null},{"id":"2405.17412","title":"Towards One Model for Classical Dimensionality Reduction: A Probabilistic Perspective on UMAP and t-SNE","created":"2024-05-27","cited_by_count":3,"area":null},{"id":"2501.13732","title":"A dimensionality reduction technique based on the Gromov-Wasserstein distance","created":"2025-01-23","cited_by_count":3,"area":null},{"id":"2307.08509","title":"Kernel-Based Testing for Single-Cell Differential Analysis","created":"2023-07-17","cited_by_count":2,"area":null},{"id":"2310.03398","title":"Interpolating between Clustering and Dimensionality Reduction with Gromov-Wasserstein","created":"2023-10-05","cited_by_count":0,"area":null},{"id":"2602.11662","title":"UMAP Is Spectral Clustering on the Fuzzy Nearest-Neighbor Graph","created":"2026-02-12","cited_by_count":0,"area":null},{"id":"2604.00485","title":"The Rashomon Effect for Visualizing High-Dimensional Data","created":"2026-04-01","cited_by_count":0,"area":null}],"next_cursor":null}