Jeremias Knoblauch

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 23

Top Topics

Bayesian Inference

Top Venues

Publications

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 (2024)
Matías Altamirano, François-Xavier Briol, Jeremias Knoblauch
Robust and Conjugate Gaussian Process Regression. CoRR (2023)
Veit David Wild, Sahra Ghalebikesabi, Dino Sejdinovic, Jeremias Knoblauch
A Rigorous Link between Deep Ensembles and (Variational) Bayesian Methods. NeurIPS (2023)
Matías Altamirano, François-Xavier Briol, Jeremias Knoblauch
Robust and Scalable Bayesian Online Changepoint Detection. CoRR (2023)
Veit David Wild, Sahra Ghalebikesabi, Dino Sejdinovic, Jeremias Knoblauch
A Rigorous Link between Deep Ensembles and (Variational) Bayesian Methods. CoRR (2023)
Matías Altamirano, François-Xavier Briol, Jeremias Knoblauch
Robust and Scalable Bayesian Online Changepoint Detection. ICML (2023)
Charita Dellaporta, Jeremias Knoblauch, Theodoros Damoulas, François-Xavier Briol
Robust Bayesian Inference for Simulator-based Models via the MMD Posterior Bootstrap. AISTATS (2022)
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 (2022)
Charita Dellaporta, Jeremias Knoblauch, Theodoros Damoulas, François-Xavier Briol
Robust Bayesian Inference for Simulator-based Models via the MMD Posterior Bootstrap. CoRR (2022)
Hisham Husain, Jeremias Knoblauch
Adversarial Interpretation of Bayesian Inference. ALT (2022)
Jeremias Knoblauch, Jack Jewson, Theodoros Damoulas
An Optimization-centric View on Bayes' Rule: Reviewing and Generalizing Variational Inference. J. Mach. Learn. Res. 23 (2022)
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 (2022)
Juan Maroñas, Oliver Hamelijnck, Jeremias Knoblauch, Theodoros Damoulas
Transforming Gaussian Processes With Normalizing Flows. AISTATS (2021)
Jeremias Knoblauch, Hisham Husain, Tom Diethe
Optimal Continual Learning has Perfect Memory and is NP-hard. CoRR (2020)
Juan Maroñas, Oliver Hamelijnck, Jeremias Knoblauch, Theodoros Damoulas
Transforming Gaussian Processes With Normalizing Flows. CoRR (2020)
Jeremias Knoblauch, Hisham Husain, Tom Diethe
Optimal Continual Learning has Perfect Memory and is NP-hard. ICML (2020)
Jeremias Knoblauch, Lara Vomfell
Robust Bayesian Inference for Discrete Outcomes with the Total Variation Distance. CoRR (2020)
Jeremias Knoblauch, Jack Jewson, Theodoros Damoulas
Generalized Variational Inference. CoRR (2019)
Jeremias Knoblauch
Robust Deep Gaussian Processes. CoRR (2019)
Jeremias Knoblauch, Jack Jewson, Theodoros Damoulas
Doubly Robust Bayesian Inference for Non-Stationary Streaming Data with β-Divergences. CoRR (2018)
Jeremias Knoblauch, Jack Jewson, Theodoros Damoulas
Doubly Robust Bayesian Inference for Non-Stationary Streaming Data with \beta-Divergences. NeurIPS (2018)
Jeremias Knoblauch, Theodoros Damoulas
Spatio-temporal Bayesian On-line Changepoint Detection with Model Selection. ICML (2018)
Jeremias Knoblauch, Theodoros Damoulas
Spatio-temporal Bayesian On-line Changepoint Detection with Model Selection. CoRR (2018)