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Jeremias Knoblauch
Jeremias Knoblauch
Associate professor & EPSRC Fellow @ University College London
Verified email at ucl.ac.uk - Homepage
Title
Cited by
Cited by
Year
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
256*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
1292020
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
882022
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
Spatio-temporal Bayesian on-line changepoint detection with model selection
J Knoblauch, T Damoulas
International Conference on Machine Learning, 2718-2727, 2018
682018
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
472022
Transforming Gaussian processes with normalizing flows
J Maroñas, O Hamelijnck, J Knoblauch, T Damoulas
International Conference on Artificial Intelligence and Statistics, 1081-1089, 2021
432021
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
302020
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
212024
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
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
152023
Robust and conjugate Gaussian process regression
M Altamirano, FX Briol, J Knoblauch
arXiv preprint arXiv:2311.00463, 2023
152023
Adversarial interpretation of Bayesian inference
H Husain, J Knoblauch
International Conference on Algorithmic Learning Theory, 553-572, 2022
122022
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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