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Jeremias Knoblauch
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2020 – today
- 2024
- [c10]Matías Altamirano, François-Xavier Briol, Jeremias Knoblauch:
Robust and Conjugate Gaussian Process Regression. ICML 2024 - [c9]Gerardo Duran-Martin, Matías Altamirano, Alexander Y. Shestopaloff, Leandro Sánchez-Betancourt, Jeremias Knoblauch, Matt Jones, François-Xavier Briol, Kevin Patrick Murphy:
Outlier-robust Kalman Filtering through Generalised Bayes. ICML 2024 - [i13]Gerardo Duran-Martin, Matías Altamirano, Alexander Y. Shestopaloff, Leandro Sánchez-Betancourt, Jeremias Knoblauch, Matt Jones, François-Xavier Briol, Kevin Murphy:
Outlier-robust Kalman Filtering through Generalised Bayes. CoRR abs/2405.05646 (2024) - 2023
- [c8]Matías Altamirano, François-Xavier Briol, Jeremias Knoblauch:
Robust and Scalable Bayesian Online Changepoint Detection. ICML 2023: 642-663 - [c7]Veit David Wild, Sahra Ghalebikesabi, Dino Sejdinovic, Jeremias Knoblauch:
A Rigorous Link between Deep Ensembles and (Variational) Bayesian Methods. NeurIPS 2023 - [i12]Matías Altamirano, François-Xavier Briol, Jeremias Knoblauch:
Robust and Scalable Bayesian Online Changepoint Detection. CoRR abs/2302.04759 (2023) - [i11]Veit David Wild, Sahra Ghalebikesabi, Dino Sejdinovic, Jeremias Knoblauch:
A Rigorous Link between Deep Ensembles and (Variational) Bayesian Methods. CoRR abs/2305.15027 (2023) - [i10]Matías Altamirano, François-Xavier Briol, Jeremias Knoblauch:
Robust and Conjugate Gaussian Process Regression. CoRR abs/2311.00463 (2023) - 2022
- [j2]Joel Jaskari
, Jaakko Sahlsten
, Theodoros Damoulas, Jeremias Knoblauch, Simo Särkkä
, Leo Kärkkäinen
, Kustaa Hietala, Kimmo K. Kaski
:
Uncertainty-Aware Deep Learning Methods for Robust Diabetic Retinopathy Classification. IEEE Access 10: 76669-76681 (2022) - [j1]Jeremias Knoblauch, Jack Jewson, Theodoros Damoulas:
An Optimization-centric View on Bayes' Rule: Reviewing and Generalizing Variational Inference. J. Mach. Learn. Res. 23: 132:1-132:109 (2022) - [c6]Charita Dellaporta, Jeremias Knoblauch, Theodoros Damoulas, François-Xavier Briol:
Robust Bayesian Inference for Simulator-based Models via the MMD Posterior Bootstrap. AISTATS 2022: 943-970 - [c5]Hisham Husain, Jeremias Knoblauch:
Adversarial Interpretation of Bayesian Inference. ALT 2022: 553-572 - [i9]Joel Jaskari, Jaakko Sahlsten, Theodoros Damoulas, Jeremias Knoblauch, Simo Särkkä, Leo Kärkkäinen, Kustaa Hietala, Kimmo Kaski:
Uncertainty-aware deep learning methods for robust diabetic retinopathy classification. CoRR abs/2201.09042 (2022) - [i8]Charita Dellaporta, Jeremias Knoblauch, Theodoros Damoulas, François-Xavier Briol:
Robust Bayesian Inference for Simulator-based Models via the MMD Posterior Bootstrap. CoRR abs/2202.04744 (2022) - 2021
- [b1]Jeremias Knoblauch:
Optimization-centric generalizations of Bayesian inference. University of Warwick, Coventry, UK, 2021 - [c4]Juan Maroñas, Oliver Hamelijnck, Jeremias Knoblauch, Theodoros Damoulas:
Transforming Gaussian Processes With Normalizing Flows. AISTATS 2021: 1081-1089 - 2020
- [c3]Jeremias Knoblauch, Hisham Husain, Tom Diethe:
Optimal Continual Learning has Perfect Memory and is NP-hard. ICML 2020: 5327-5337 - [i7]Jeremias Knoblauch, Hisham Husain, Tom Diethe:
Optimal Continual Learning has Perfect Memory and is NP-hard. CoRR abs/2006.05188 (2020) - [i6]Jeremias Knoblauch, Lara Vomfell:
Robust Bayesian Inference for Discrete Outcomes with the Total Variation Distance. CoRR abs/2010.13456 (2020) - [i5]Juan Maroñas, Oliver Hamelijnck, Jeremias Knoblauch, Theodoros Damoulas:
Transforming Gaussian Processes With Normalizing Flows. CoRR abs/2011.01596 (2020)
2010 – 2019
- 2019
- [i4]Jeremias Knoblauch, Jack Jewson, Theodoros Damoulas:
Generalized Variational Inference. CoRR abs/1904.02063 (2019) - [i3]Jeremias Knoblauch:
Robust Deep Gaussian Processes. CoRR abs/1904.02303 (2019) - 2018
- [c2]Jeremias Knoblauch, Theodoros Damoulas:
Spatio-temporal Bayesian On-line Changepoint Detection with Model Selection. ICML 2018: 2723-2732 - [c1]Jeremias Knoblauch, Jack Jewson, Theodoros Damoulas:
Doubly Robust Bayesian Inference for Non-Stationary Streaming Data with \beta-Divergences. NeurIPS 2018: 64-75 - [i2]Jeremias Knoblauch, Theodoros Damoulas:
Spatio-temporal Bayesian On-line Changepoint Detection with Model Selection. CoRR abs/1805.05383 (2018) - [i1]Jeremias Knoblauch, Jack Jewson, Theodoros Damoulas:
Doubly Robust Bayesian Inference for Non-Stationary Streaming Data with β-Divergences. CoRR abs/1806.02261 (2018)
Coauthor Index

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last updated on 2024-10-07 21:16 CEST by the dblp team
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