ML Anthology

Kurle, Richard

12 publications

TMLR 2025 AB-UPT: Scaling Neural CFD Surrogates for High- Fidelity Automotive Aerodynamics Simulations via Anchored- Branched Universal Physics Transformers Benedikt Alkin, Maurits Bleeker, Richard Kurle, Tobias Kronlachner, Reinhard Sonnleitner, Matthias Dorfer, Johannes Brandstetter
ICML 2025 xLSTM 7b: A Recurrent LLM for Fast and Efficient Inference Maximilian Beck, Korbinian Pöppel, Phillip Lippe, Richard Kurle, Patrick M Blies, Günter Klambauer, Sebastian Böck, Sepp Hochreiter
ICLRW 2025 xLSTM 7b: A Recurrent LLM for Fast and Efficient Inference Maximilian Beck, Korbinian Pöppel, Phillip Lippe, Richard Kurle, Patrick M Blies, Günter Klambauer, Sebastian Böck, Sepp Hochreiter
NeurIPS 2022 On the Detrimental Effect of Invariances in the Likelihood for Variational Inference Richard Kurle, Ralf Herbrich, Tim Januschowski, Yuyang Wang, Jan Gasthaus
NeurIPS 2021 Deep Explicit Duration Switching Models for Time Series Abdul Fatir Ansari, Konstantinos Benidis, Richard Kurle, Ali Caner Turkmen, Harold Soh, Alexander J Smola, Bernie Wang, Tim Januschowski
NeurIPS 2021 Latent Matters: Learning Deep State-Space Models Alexej Klushyn, Richard Kurle, Maximilian Soelch, Botond Cseke, Patrick van der Smagt
ICLR 2020 Continual Learning with Bayesian Neural Networks for Non-Stationary Data Richard Kurle, Botond Cseke, Alexej Klushyn, Patrick van der Smagt, Stephan Günnemann
NeurIPS 2020 Deep Rao-Blackwellised Particle Filters for Time Series Forecasting Richard Kurle, Syama Sundar Rangapuram, Emmanuel de Bézenac, Stephan Günnemann, Jan Gasthaus
NeurIPS 2020 Normalizing Kalman Filters for Multivariate Time Series Analysis Emmanuel de Bézenac, Syama Sundar Rangapuram, Konstantinos Benidis, Michael Bohlke-Schneider, Richard Kurle, Lorenzo Stella, Hilaf Hasson, Patrick Gallinari, Tim Januschowski
NeurIPS 2019 Learning Hierarchical Priors in VAEs Alexej Klushyn, Nutan Chen, Richard Kurle, Botond Cseke, Patrick van der Smagt
AAAI 2019 Multi-Source Neural Variational Inference Richard Kurle, Stephan Günnemann, Patrick van der Smagt
AISTATS 2018 Metrics for Deep Generative Models Nutan Chen, Alexej Klushyn, Richard Kurle, Xueyan Jiang, Justin Bayer, Patrick van der Smagt