עקוב אחר
Jeremias Knoblauch
Jeremias Knoblauch
Associate professor & EPSRC Fellow @ University College London
כתובת אימייל מאומתת בדומיין ucl.ac.uk - דף הבית
כותרת
צוטט על ידי
צוטט על ידי
שנה
An optimization-centric view on Bayes' rule: Reviewing and generalizing variational inference‏
J Knoblauch, J Jewson, T Damoulas‏
Journal of Machine Learning Research 23 (132), 1-109, 2022‏
252*2022
Optimal continual learning has perfect memory and is np-hard‏
J Knoblauch, H Husain, T Diethe‏
International Conference on Machine Learning, 5327-5337, 2020‏
1272020
Doubly Robust Bayesian Inference for Non-Stationary Streaming Data with -Divergences‏
J Knoblauch, JE Jewson, T Damoulas‏
Advances in Neural Information Processing Systems 31, 2018‏
862018
Robust generalised Bayesian inference for intractable likelihoods‏
T Matsubara, J Knoblauch, FX Briol, CJ Oates‏
Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2022‏
842022
Spatio-temporal Bayesian on-line changepoint detection with model selection‏
J Knoblauch, T Damoulas‏
International Conference on Machine Learning, 2718-2727, 2018‏
672018
Robust Bayesian inference for simulator-based models via the MMD posterior bootstrap‏
C Dellaporta, J Knoblauch, T Damoulas, FX Briol‏
International Conference on Artificial Intelligence and Statistics, 943-970, 2022‏
432022
Transforming Gaussian processes with normalizing flows‏
J Maroñas, O Hamelijnck, J Knoblauch, T Damoulas‏
International Conference on Artificial Intelligence and Statistics, 1081-1089, 2021‏
412021
Uncertainty-aware deep learning methods for robust diabetic retinopathy classification‏
J Jaskari, J Sahlsten, T Damoulas, J Knoblauch, S Särkkä, L Kärkkäinen, ...‏
IEEE Access 10, 76669-76681, 2022‏
362022
Generalized posteriors in approximate Bayesian computation‏
SM Schmon, PW Cannon, J Knoblauch‏
arXiv preprint arXiv:2011.08644, 2020‏
292020
Generalized Bayesian inference for discrete intractable likelihood‏
T Matsubara, J Knoblauch, FX Briol, CJ Oates‏
Journal of the American Statistical Association 119 (547), 2345-2355, 2024‏
202024
Robust and scalable Bayesian online changepoint detection‏
M Altamirano, FX Briol, J Knoblauch‏
International Conference on Machine Learning, 642-663, 2023‏
192023
Robust Deep Gaussian Processes‏
J Knoblauch‏
arXiv preprint arXiv:1904.02303, 2019‏
182019
Robust and conjugate Gaussian process regression‏
M Altamirano, FX Briol, J Knoblauch‏
arXiv preprint arXiv:2311.00463, 2023‏
152023
A rigorous link between deep ensembles and (variational) Bayesian methods‏
VD Wild, S Ghalebikesabi, D Sejdinovic, J Knoblauch‏
Advances in Neural Information Processing Systems 36, 39782-39811, 2023‏
132023
Adversarial interpretation of Bayesian inference‏
H Husain, J Knoblauch‏
International Conference on Algorithmic Learning Theory, 553-572, 2022‏
132022
Frequentist consistency of generalized variational inference‏
J Knoblauch‏
arXiv preprint arXiv:1912.04946, 2019‏
112019
Outlier-robust Kalman filtering through generalised Bayes‏
G Duran-Martin, M Altamirano, AY Shestopaloff, L Sanchez Betancourt, ...‏
102024
Robust Bayesian inference for discrete outcomes with the total variation distance‏
J Knoblauch, L Vomfell‏
arXiv preprint arXiv:2010.13456, 2020‏
102020
Robustifying likelihoods by optimistically re-weighting data‏
M Dewaskar, C Tosh, J Knoblauch, DB Dunson‏
Journal of the American Statistical Association, 1-23, 2025‏
62025
The impact of loss estimation on Gibbs measures‏
DT Frazier, J Knoblauch, C Drovandi‏
arXiv preprint arXiv:2404.15649, 2024‏
42024
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מאמרים 1–20