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Disentangled multi-fidelity deep bayesian active learning. In International Conference on Machine Learning

Wu, D; Niu, R; Chinazzi, M; Ma, Y; Yu, R (July 2023, PMLR)

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Deep Bayesian active learning for accelerating stochastic simulation. In Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (pp. 2559-2569).

Wu, D; Niu, R; Chinazzi, M; Vespignani, A; Ma, YA; Yu, R (August 2023, ACM Digital Library)

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Multi-fidelity Hierarchical Neural Processes

https://doi.org/10.1145/3534678.3539364

Wu, D; Chinazzi, M.; Ma, Y-A; Yu, R. (January 2022, ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD))

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Multi-fidelity Hierarchical Neural Processes

Wu, D.; Chinazzi, M.; Vespignani, A.; Ma, Y.A.; Yu, R. (January 2022, ArXivorg)

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Quantifying uncertainty in deep spatiotemporal forecasting.

https://doi.org/10.1145/3447548.3467325

Wu, D.; Gao, L.; Xiong, X.; Chinazzi, M.; Vespignani, A.; Ma, Y.A.; Yu, R. (January 2021, ArXivorg)

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