Representation Learning via Variational Bayesian Networks

Author:

Barkan Oren1,Caciularu Avi2,Rejwan Idan3,Katz Ori4,Weill Jonathan5,Malkiel Itzik6,Koenigstein Noam7

Affiliation:

1. The Open University & Microsoft, Tel-Aviv, Israel

2. Bar-Ilan University, Ramat Gan, Israel

3. AI21 Labs, Tel-Aviv, Israel

4. Microsoft & Technion, Tel-Aviv, Israel

5. Microsoft, Tel-Aviv, Israel

6. Microsoft & Tel-Aviv University, Tel-Aviv, Israel

7. Microsof & Tel-Aviv University, Tel-Aviv, Israel

Publisher

ACM

Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. TransDrift: Modeling Word-Embedding Drift using Transformer;Companion Proceedings of the ACM Web Conference 2024;2024-05-13

2. A Counterfactual Framework for Learning and Evaluating Explanations for Recommender Systems;Proceedings of the ACM Web Conference 2024;2024-05-13

3. Efficient Discovery and Effective Evaluation of Visual Perceptual Similarity: A Benchmark and Beyond;2023 IEEE/CVF International Conference on Computer Vision (ICCV);2023-10-01

4. Modeling users’ heterogeneous taste with diversified attentive user profiles;User Modeling and User-Adapted Interaction;2023-08-01

5. Metricbert: Text Representation Learning Via Self-Supervised Triplet Training;ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2022-05-23

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