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Active Learning in Gaussian Process State Space Model.

, , , , and . ECML/PKDD (3), volume 12977 of Lecture Notes in Computer Science, page 346-361. Springer, (2021)

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Structural Kernel Search via Bayesian Optimization and Symbolical Optimal Transport., , and . NeurIPS, (2022)Batch Active Learning in Gaussian Process Regression using Derivatives., , and . CoRR, (2024)A posteriori error estimation for parabolic problems with dynamic boundary conditions., and . CoRR, (2023)Amortized Inference for Gaussian Process Hyperparameters of Structured Kernels., , and . UAI, volume 216 of Proceedings of Machine Learning Research, page 184-194. PMLR, (2023)Future Aware Safe Active Learning of Time Varying Systems using Gaussian Processes., and . CoRR, (2024)Safe Active Learning for Time-Series Modeling with Gaussian Processes., , and . NeurIPS, page 2735-2744. (2018)Safe Active Learning for Time-Series Modeling with Gaussian Processes., , and . GI-Jahrestagung, volume P-294 of LNI, page 281. GI, (2019)Hierarchical-Hyperplane Kernels for Actively Learning Gaussian Process Models of Nonstationary Systems., , and . AISTATS, volume 206 of Proceedings of Machine Learning Research, page 7897-7912. PMLR, (2023)A new efficient approach to fit stochastic models on the basis of high-throughput experimental data using a model of IRF7 gene expression as case study., , and . BMC Syst. Biol., 11 (1): 26:1-26:14 (2017)Efficiently Computable Safety Bounds for Gaussian Processes in Active Learning., , , , and . AISTATS, volume 238 of Proceedings of Machine Learning Research, page 1333-1341. PMLR, (2024)