{"total":16,"rows":[{"id":"2203.01570","title":"Representing Mixtures of Word Embeddings with Mixtures of Topic Embeddings","created":"2022-03-03","cited_by_count":36,"area":null},{"id":"2101.01100","title":"Wasserstein barycenters are NP-hard to compute","created":"2021-01-04","cited_by_count":28,"area":null},{"id":"2307.01226","title":"vONTSS: vMF based semi-supervised neural topic modeling with optimal transport","created":"2023-07-03","cited_by_count":16,"area":null},{"id":"2105.14403","title":"Re-evaluating Word Mover's Distance","created":"2021-05-30","cited_by_count":10,"area":null},{"id":"2109.03431","title":"Fixed Support Tree-Sliced Wasserstein Barycenter","created":"2021-09-08","cited_by_count":10,"area":null},{"id":"2201.12195","title":"Measure Estimation in the Barycentric Coding Model","created":"2022-01-28","cited_by_count":9,"area":null},{"id":"2212.00133","title":"Universal Neural Optimal Transport","created":"2022-11-30","cited_by_count":6,"area":null},{"id":"2209.14228","title":"Knowledge-Aware Bayesian Deep Topic Model","created":"2022-09-20","cited_by_count":5,"area":null},{"id":"2310.11256","title":"Gromov-Wasserstein-like Distances in the Gaussian Mixture Models Space","created":"2023-10-17","cited_by_count":4,"area":null},{"id":"2111.01023","title":"Interpretable contrastive word mover's embedding","created":"2021-11-01","cited_by_count":2,"area":null},{"id":"2112.07259","title":"TopNet: Learning from Neural Topic Model to Generate Long Stories","created":"2021-12-14","cited_by_count":2,"area":null},{"id":"2211.14923","title":"Unsupervised Opinion Summarisation in the Wasserstein Space","created":"2022-11-27","cited_by_count":2,"area":null},{"id":"2209.00232","title":"Hybrid Gromov-Wasserstein Embedding for Capsule Learning","created":"2022-09-01","cited_by_count":1,"area":null},{"id":"2410.23602","title":"Linearized Wasserstein Barycenters: Synthesis, Analysis, Representational Capacity, and Applications","created":"2024-10-31","cited_by_count":1,"area":null},{"id":"2102.03525","title":"Exclusive Topic Modeling","created":"2021-02-06","cited_by_count":0,"area":null},{"id":"2102.04449","title":"Concentrated Document Topic Model","created":"2021-02-06","cited_by_count":0,"area":null}],"next_cursor":null}