Richard Kurle - RankMe

23 papers A* 9A 1Journal 12

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Latent Matters: Learning Deep State-Space Models. CoRR Alexej Klushyn, Richard Kurle, Maximilian Soelch, Botond Cseke, Patrick van der Smagt
2025	J	`jnl`	AB-UPT for Automotive and Aerospace Applications. CoRR Benedikt Alkin, Richard Kurle, Louis Serrano, Dennis Just, Johannes Brandstetter
2025	J	`jnl`	AB-UPT: Scaling Neural CFD Surrogates for High- Fidelity Automotive Aerodynamics Simulations via Anchored- Branched Universal Physics Transformers. Trans. Mach. Learn. Res. Benedikt Alkin, Maurits Bleeker, Richard Kurle, Tobias Kronlachner, Reinhard Sonnleitner, Matthias Dorfer, Johannes Brandstetter
2025	J	`jnl`	Going with the Speed of Sound: Pushing Neural Surrogates into Highly-turbulent Transonic Regimes. CoRR Fabian Paischer, Léo Cotteleer, Yann Dreze, Richard Kurle, Dylan Rubini, Maurits Bleeker, Tobias Kronlachner, Johannes Brandstetter
2025	A*	`conf`	xLSTM 7B: A Recurrent LLM for Fast and Efficient Inference. ICML Maximilian Beck, Korbinian Pöppel, Phillip Lippe, Richard Kurle, Patrick M. Blies, Günter Klambauer, Sebastian Böck, Sepp Hochreiter
2025	J	`jnl`	xLSTM 7B: A Recurrent LLM for Fast and Efficient Inference. CoRR Maximilian Beck, Korbinian Pöppel, Phillip Lippe, Richard Kurle, Patrick M. Blies, Günter Klambauer, Sebastian Böck, Sepp Hochreiter
2024	J	`jnl`	BALI: Learning Neural Networks via Bayesian Layerwise Inference. CoRR Richard Kurle, Alexej Klushyn, Ralf Herbrich
2023	—	`—`	Variational Bayes for Continual Learning and Time-Series Forecasting. Richard Kurle
2022	J	`jnl`	Intrinsic Anomaly Detection for Multi-Variate Time Series. CoRR Stephan Rabanser, Tim Januschowski, Kashif Rasul, Oliver Borchert, Richard Kurle, Jan Gasthaus, Michael Bohlke-Schneider, Nicolas Papernot, Valentin Flunkert
2022	A*	`conf`	On the detrimental effect of invariances in the likelihood for variational inference. NeurIPS Richard Kurle, Ralf Herbrich, Tim Januschowski, Yuyang Wang, Jan Gasthaus
2022	J	`jnl`	On the detrimental effect of invariances in the likelihood for variational inference. CoRR Richard Kurle, Ralf Herbrich, Tim Januschowski, Yuyang Wang, Jan Gasthaus
2021	A*	`conf`	Deep Explicit Duration Switching Models for Time Series. NeurIPS Abdul Fatir Ansari, Konstantinos Benidis, Richard Kurle, Ali Caner Türkmen, Harold Soh, Alexander J. Smola, Bernie Wang, Tim Januschowski
2021	J	`jnl`	Deep Explicit Duration Switching Models for Time Series. CoRR Abdul Fatir Ansari, Konstantinos Benidis, Richard Kurle, Ali Caner Türkmen, Harold Soh, Alexander J. Smola, Yuyang Wang, Tim Januschowski
2021	A*	`conf`	Latent Matters: Learning Deep State-Space Models. NeurIPS Alexej Klushyn, Richard Kurle, Maximilian Soelch, Botond Cseke, Patrick van der Smagt
2020	A*	`conf`	Continual Learning with Bayesian Neural Networks for Non-Stationary Data. ICLR Richard Kurle, Botond Cseke, Alexej Klushyn, Patrick van der Smagt, Stephan Günnemann
2020	A*	`conf`	Deep Rao-Blackwellised Particle Filters for Time Series Forecasting. NeurIPS Richard Kurle, Syama Sundar Rangapuram, Emmanuel de Bézenac, Stephan Günnemann, Jan Gasthaus
2020	A*	`conf`	Normalizing Kalman Filters for Multivariate Time Series Analysis. NeurIPS Emmanuel de Bézenac, Syama Sundar Rangapuram, Konstantinos Benidis, Michael Bohlke-Schneider, Richard Kurle, Lorenzo Stella, Hilaf Hasson, Patrick Gallinari, Tim Januschowski
2019	A*	`conf`	Learning Hierarchical Priors in VAEs. NeurIPS Alexej Klushyn, Nutan Chen, Richard Kurle, Botond Cseke, Patrick van der Smagt
2019	J	`jnl`	Learning Hierarchical Priors in VAEs. CoRR Alexej Klushyn, Nutan Chen, Richard Kurle, Botond Cseke, Patrick van der Smagt
2019	A*	`conf`	Multi-Source Neural Variational Inference. AAAI Richard Kurle, Stephan Günnemann, Patrick van der Smagt
2018	A	`conf`	Metrics for Deep Generative Models. AISTATS Nutan Chen, Alexej Klushyn, Richard Kurle, Xueyan Jiang, Justin Bayer, Patrick van der Smagt
2018	J	`jnl`	Multi-Source Neural Variational Inference. CoRR Richard Kurle, Stephan Günnemann, Patrick van der Smagt
2017	J	`jnl`	Metrics for Deep Generative Models. CoRR Nutan Chen, Alexej Klushyn, Richard Kurle, Xueyan Jiang, Justin Bayer, Patrick van der Smagt