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Deep State-Space Generative Model For Correlated Time-to-Event Predictions.

, , , , , , и . KDD, стр. 1552-1562. ACM, (2020)

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Andrew M Gaskievicz

Jing Dai

Huangdong Dai

Yangguang Dai

Min Dai

 

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Many Paths to Equilibrium: GANs Do Not Need to Decrease a Divergence At Every Step., , , , , и . ICLR (Poster), OpenReview.net, (2018)Scalable and accurate deep learning for electronic health records., , , , , , , , , и 24 other автор(ы). CoRR, (2018)Reply: metrics to assess machine learning models., , , , , , и . npj Digit. Medicine, (2018)Scalable and accurate deep learning with electronic health records., , , , , , , , , и 25 other автор(ы). npj Digit. Medicine, (2018)MUFASA: Multimodal Fusion Architecture Search for Electronic Health Records., , и . AAAI, стр. 10532-10540. AAAI Press, (2021)Compositionality and Capacity in Emergent Languages., , , , и . RepL4NLP@ACL, стр. 34-38. Association for Computational Linguistics, (2020)Deep State-Space Generative Model For Correlated Time-to-Event Predictions., , , , , , и . KDD, стр. 1552-1562. ACM, (2020)MaMMUT: A Simple Architecture for Joint Learning for MultiModal Tasks., , , , , , , , , и 2 other автор(ы). Trans. Mach. Learn. Res., (2023)Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models., , , , , , , , , и 440 other автор(ы). CoRR, (2022)Learning to Select the Best Forecasting Tasks for Clinical Outcome Prediction., , , , и . CoRR, (2024)