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Richard Kurle
Tytuł
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Metrics for deep generative models
N Chen, A Klushyn, R Kurle, X Jiang, J Bayer, P Smagt
International Conference on Artificial Intelligence and Statistics, 1540-1550, 2018
1382018
Normalizing kalman filters for multivariate time series analysis
E de Bézenac, SS Rangapuram, K Benidis, M Bohlke-Schneider, R Kurle, ...
Advances in Neural Information Processing Systems 33, 2995-3007, 2020
1272020
Learning hierarchical priors in vaes
A Klushyn, N Chen, R Kurle, B Cseke, P van der Smagt
Advances in neural information processing systems 32, 2019
1102019
Continual learning with bayesian neural networks for non-stationary data
R Kurle, B Cseke, A Klushyn, P Van Der Smagt, S Günnemann
International Conference on Learning Representations, 2019
802019
I hear you eat and speak: Automatic recognition of eating condition and food type, use-cases, and impact on asr performance
S Hantke, F Weninger, R Kurle, F Ringeval, A Batliner, AED Mousa, ...
PloS one 11 (5), e0154486, 2016
492016
Latent matters: Learning deep state-space models
A Klushyn, R Kurle, M Soelch, B Cseke, P van der Smagt
Advances in Neural Information Processing Systems 34, 10234-10245, 2021
402021
Deep rao-blackwellised particle filters for time series forecasting
R Kurle, SS Rangapuram, E de Bézenac, S Günnemann, J Gasthaus
Advances in Neural Information Processing Systems 33, 15371-15382, 2020
362020
Multi-source neural variational inference
R Kurle, S Günnemann, P Van der Smagt
Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 4114-4121, 2019
302019
Deep explicit duration switching models for time series
AF Ansari, K Benidis, R Kurle, AC Turkmen, H Soh, AJ Smola, B Wang, ...
Advances in Neural Information Processing Systems 34, 29949-29961, 2021
282021
On the detrimental effect of invariances in the likelihood for variational inference
R Kurle, R Herbrich, T Januschowski, Y Wang, J Gasthaus
Advances in Neural Information Processing Systems 35, 2022
102022
I hear you eat and speak: automatic recognition of eating condition and food type
S Hantke, F Weninger, R Kurle, A Batliner, B Schuller
to appear, 2015
102015
On symmetries in variational Bayesian neural nets
R Kurle, T Januschowski, J Gasthaus, YB Wang
62021
Intrinsic Anomaly Detection for Multi-Variate Time Series
S Rabanser, T Januschowski, K Rasul, O Borchert, R Kurle, J Gasthaus, ...
arXiv preprint arXiv:2206.14342, 2022
42022
Metrics for deep generative models based on learned skills
N Chen, A Klushyn, R Kurle, X Jiang, J Bayer, P van der Smagt
Advances in Neural Information Processing Systems (NIPS) Workshop on …, 2017
22017
BALI: Learning Neural Networks via Bayesian Layerwise Inference
R Kurle, A Klushyn, R Herbrich
arXiv preprint arXiv:2411.12102, 2024
2024
Variational Bayes for Continual Learning and Time-Series Forecasting
R Kurle
Technische Universität München, 2023
2023
Context-invariant, multi-variate time series representations
S Rabanser, T Januschowski, K Rasul, O Borchert, R Kurle, J Gasthaus, ...
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