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Physically-Inspired Gaussian Process Models for Post-Transcriptional Regulation in Drosophila.

, , and . IEEE ACM Trans. Comput. Biol. Bioinform., 18 (2): 656-666 (2021)

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Finite-dimensional Gaussian approximation with linear inequality constraints., , , and . CoRR, (2017)High-dimensional Additive Gaussian Processes under Monotonicity Constraints., , and . NeurIPS, (2022)Sparse Linear Models Applied to Power Quality Disturbance Classification., , and . CIARP, volume 10125 of Lecture Notes in Computer Science, page 521-529. (2016)Finite-Dimensional Gaussian Approximation with Linear Inequality Constraints., , , and . SIAM/ASA J. Uncertain. Quantification, 6 (3): 1224-1255 (2018)Improving Diffusion Tensor Estimation Using Adaptive and Optimized Filtering Based on Local Similarity., , and . IbPRIA, volume 9117 of Lecture Notes in Computer Science, page 612-620. Springer, (2015)Approximating Gaussian Process Emulators with Linear Inequality Constraints and Noisy Observations via MC and MCMC., , , and . CoRR, (2019)Physically-Inspired Gaussian Process Models for Post-Transcriptional Regulation in Drosophila., , and . IEEE ACM Trans. Comput. Biol. Bioinform., 18 (2): 656-666 (2021)Switched Latent Force Models for Reverse-Engineering Transcriptional Regulation in Gene Expression Data., and . IEEE ACM Trans. Comput. Biol. Bioinform., 16 (1): 322-335 (2019)Multi-Output Gaussian Processes with Functional Data: A Study on Coastal Flood Hazard Assessment., , , and . CoRR, (2020)Gaussian Process Modulated Cox Processes under Linear Inequality Constraints., , and . AISTATS, volume 89 of Proceedings of Machine Learning Research, page 1997-2006. PMLR, (2019)