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ORCIDFabio Sigrist
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2020 – today
- 2024
[i8]Tim Gyger, Reinhard Furrer, Fabio Sigrist:
Iterative Methods for Full-Scale Gaussian Process Approximations for Large Spatial Data. CoRR abs/2405.14492 (2024)- [i7]Pascal Kündig, Fabio Sigrist:
A Spatio-Temporal Machine Learning Model for Mortgage Credit Risk: Default Probabilities and Loan Portfolios. CoRR abs/2410.02846 (2024) - 2023
- [j6]Fabio Sigrist
, Nicola Leuenberger:
Machine learning for corporate default risk: Multi-period prediction, frailty correlation, loan portfolios, and tail probabilities. Eur. J. Oper. Res. 305(3): 1390-1406 (2023) - [j5]Fabio Sigrist:
Latent Gaussian Model Boosting. IEEE Trans. Pattern Anal. Mach. Intell. 45(2): 1894-1905 (2023) - [i6]Fabio Sigrist:
A Comparison of Machine Learning Methods for Data with High-Cardinality Categorical Variables. CoRR abs/2307.02071 (2023) - [i5]Pascal Kündig, Fabio Sigrist:
Iterative Methods for Vecchia-Laplace Approximations for Latent Gaussian Process Models. CoRR abs/2310.12000 (2023) - 2022
- [j4]Jakob A. Dambon, Fabio Sigrist, Reinhard Furrer:
Joint variable selection of both fixed and random effects for Gaussian process-based spatially varying coefficient models. Int. J. Geogr. Inf. Sci. 36(12): 2525-2548 (2022) - [j3]Fabio Sigrist:
Gaussian Process Boosting. J. Mach. Learn. Res. 23: 232:1-232:46 (2022) - 2021
- [j2]Fabio Sigrist:
Gradient and Newton boosting for classification and regression. Expert Syst. Appl. 167: 114080 (2021) - [j1]Fabio Sigrist:
KTBoost: Combined Kernel and Tree Boosting. Neural Process. Lett. 53(2): 1147-1160 (2021) - [i4]Fabio Sigrist:
Latent Gaussian Model Boosting. CoRR abs/2105.08966 (2021) - 2020
- [i3]Fabio Sigrist:
Gaussian Process Boosting. CoRR abs/2004.02653 (2020)
2010 – 2019
- 2019
- [i2]Fabio Sigrist:
KTBoost: Combined Kernel and Tree Boosting. CoRR abs/1902.03999 (2019) - 2018
- [i1]Fabio Sigrist:
Gradient and Newton Boosting for Classification and Regression. CoRR abs/1808.03064 (2018)
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