Stefan T. Radev

46 papers A* 2A 2Journal 40Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Amortized Bayesian Workflow. Trans. Mach. Learn. Res. Chengkun Li, Aki Vehtari, Paul-Christian Bürkner, Stefan T. Radev, Luigi Acerbi, Marvin Schmitt
2026	J	`jnl`	BayesFlow 2.0: Multi-Backend Amortized Bayesian Inference in Python. CoRR Lars Kühmichel, Jerry M. Huang, Valentin Pratz, Jonas Arruda, Hans Olischläger, Daniel Habermann, Simon Kucharský, Lasse Elsemüller, Aayush Mishra, Niels Bracher, Svenja Jedhoff, Marvin Schmitt, Paul-Christian Bürkner, Stefan T. Radev
2026	J	`jnl`	CogFormer: Learn All Your Models Once. CoRR Jerry M. Huang, Lukas Schumacher, Niek Stevenson, Stefan T. Radev
2025	J	`jnl`	Diffusion Models in Simulation-Based Inference: A Tutorial Review. CoRR Jonas Arruda, Niels Bracher, Ullrich Köthe, Jan Hasenauer, Stefan T. Radev
2025	J	`jnl`	Does Unsupervised Domain Adaptation Improve the Robustness of Amortized Bayesian Inference? A Systematic Evaluation. CoRR Lasse Elsemüller, Valentin Pratz, Mischa von Krause, Andreas Voss, Paul-Christian Bürkner, Stefan T. Radev
2025	J	`jnl`	Does Unsupervised Domain Adaptation Improve the Robustness of Amortized Bayesian Inference? A Systematic Evaluation. Trans. Mach. Learn. Res. Lasse Elsemüller, Valentin Pratz, Mischa von Krause, Andreas Voss, Paul-Christian Bürkner, Stefan T. Radev
2025	J	`jnl`	EvidenceMoE: A Physics-Guided Mixture-of-Experts with Evidential Critics for Advancing Fluorescence Light Detection and Ranging in Scattering Media. CoRR Ismail Erbas, Ferhat Demirkiran, Karthik Swaminathan, Naigang Wang, Navid Ibtehaj Nizam, Stefan T. Radev, Kaoutar El Maghraoui, Xavier Intes, Vikas Pandey
2025	J	`jnl`	Expert-elicitation method for non-parametric joint priors using normalizing flows. Stat. Comput. Florence Bockting, Stefan T. Radev, Paul-Christian Bürkner
2025	J	`jnl`	JADAI: Jointly Amortizing Adaptive Design and Bayesian Inference. CoRR Niels Bracher, Lars Kühmichel, Desi R. Ivanova, Xavier Intes, Paul-Christian Bürkner, Stefan T. Radev
2025	J	`jnl`	Modeling multi-agent motion dynamics in immersive rooms. CoRR Mincong Huang, Stefan T. Radev
2025	J	`jnl`	Robust Amortized Bayesian Inference with Self-Consistency Losses on Unlabeled Data. CoRR Aayush Mishra, Daniel Habermann, Marvin Schmitt, Stefan T. Radev, Paul-Christian Bürkner
2025	J	`jnl`	Stable Single-Pixel Contrastive Learning for Semantic and Geometric Tasks. CoRR Leonid Pogorelyuk, Niels Bracher, Aaron Verkleeren, Lars Kühmichel, Stefan T. Radev
2025	J	`jnl`	Towards Trustworthy Amortized Bayesian Model Comparison. CoRR Simon Kucharský, Aayush Mishra, Daniel Habermann, Stefan T. Radev, Paul-Christian Bürkner
2024	J	`jnl`	Aligning Motion-Blurred Images Using Contrastive Learning on Overcomplete Pixels. CoRR Leonid Pogorelyuk, Stefan T. Radev
2024	J	`jnl`	Amortized Bayesian Multilevel Models. CoRR Daniel Habermann, Marvin Schmitt, Lars Kühmichel, Andreas Bulling, Stefan T. Radev, Paul-Christian Bürkner
2024	J	`jnl`	Amortized Bayesian Workflow (Extended Abstract). CoRR Marvin Schmitt, Chengkun Li, Aki Vehtari, Luigi Acerbi, Paul-Christian Bürkner, Stefan T. Radev
2024	J	`jnl`	Compressing Recurrent Neural Networks for FPGA-accelerated Implementation in Fluorescence Lifetime Imaging. CoRR Ismail Erbas, Vikas Pandey, Aporva Amarnath, Naigang Wang, Karthik Swaminathan, Stefan T. Radev, Xavier Intes
2024	A*	`conf`	Consistency Models for Scalable and Fast Simulation-Based Inference. NeurIPS Marvin Schmitt, Valentin Pratz, Ullrich Köthe, Paul-Christian Bürkner, Stefan T. Radev
2024	J	`jnl`	Detecting Model Misspecification in Amortized Bayesian Inference with Neural Networks: An Extended Investigation. CoRR Marvin Schmitt, Paul-Christian Bürkner, Ullrich Köthe, Stefan T. Radev
2024	A*	`conf`	Leveraging Self-Consistency for Data-Efficient Amortized Bayesian Inference. ICML Marvin Schmitt, Desi R. Ivanova, Daniel Habermann, Ullrich Köthe, Paul-Christian Bürkner, Stefan T. Radev
2024	J	`jnl`	Sensitivity-Aware Amortized Bayesian Inference. Trans. Mach. Learn. Res. Lasse Elsemüller, Hans Olischläger, Marvin Schmitt, Paul-Christian Bürkner, Ullrich Köthe, Stefan T. Radev
2024	J	`jnl`	The Simplex Projection: Lossless Visualization of 4D Compositional Data on a 2D Canvas. CoRR Marvin Schmitt, Yuga Hikida, Stefan T. Radev, Filip Sadlo, Paul-Christian Bürkner
2023	J	`jnl`	A Deep Learning Method for Comparing Bayesian Hierarchical Models. CoRR Lasse Elsemüller, Martin Schnuerch, Paul-Christian Bürkner, Stefan T. Radev
2023	J	`jnl`	Amortized Bayesian Model Comparison With Evidential Deep Learning. IEEE Trans. Neural Networks Learn. Syst. Stefan T. Radev, Marco D'Alessandro, Ulf K. Mertens, Andreas Voss, Ullrich Köthe, Paul-Christian Bürkner
2023	J	`jnl`	BayesFlow: Amortized Bayesian Workflows With Neural Networks. CoRR Stefan T. Radev, Marvin Schmitt, Lukas Schumacher, Lasse Elsemüller, Valentin Pratz, Yannik Schälte, Ullrich Köthe, Paul-Christian Bürkner
2023	J	`jnl`	BayesFlow: Amortized Bayesian Workflows With Neural Networks. J. Open Source Softw. Stefan T. Radev, Marvin Schmitt, Lukas Schumacher, Lasse Elsemüller, Valentin Pratz, Yannik Schälte, Ullrich Köthe, Paul-Christian Bürkner
2023	J	`jnl`	Consistency Models for Scalable and Fast Simulation-Based Inference. CoRR Marvin Schmitt, Valentin Pratz, Ullrich Köthe, Paul-Christian Bürkner, Stefan T. Radev
2023	—	`conf`	Detecting Model Misspecification in Amortized Bayesian Inference with Neural Networks. DAGM Marvin Schmitt, Paul-Christian Bürkner, Ullrich Köthe, Stefan T. Radev
2023	J	`jnl`	Finding Competence Regions in Domain Generalization. CoRR Jens Müller, Stefan T. Radev, Robert Schmier, Felix Draxler, Carsten Rother, Ullrich Köthe
2023	J	`jnl`	Finding Competence Regions in Domain Generalization. Trans. Mach. Learn. Res. Jens Müller, Stefan T. Radev, Robert Schmier, Felix Draxler, Carsten Rother, Ullrich Köthe
2023	J	`jnl`	Fuse It or Lose It: Deep Fusion for Multimodal Simulation-Based Inference. CoRR Marvin Schmitt, Stefan T. Radev, Paul-Christian Bürkner
2023	J	`jnl`	JANA: Jointly Amortized Neural Approximation of Complex Bayesian Models. CoRR Stefan T. Radev, Marvin Schmitt, Valentin Pratz, Umberto Picchini, Ullrich Köthe, Paul-Christian Bürkner
2023	A	`conf`	Jana: Jointly amortized neural approximation of complex Bayesian models. UAI Stefan T. Radev, Marvin Schmitt, Valentin Pratz, Umberto Picchini, Ullrich Köthe, Paul-Christian Bürkner
2023	J	`jnl`	Leveraging Self-Consistency for Data-Efficient Amortized Bayesian Inference. CoRR Marvin Schmitt, Daniel Habermann, Paul-Christian Bürkner, Ullrich Köthe, Stefan T. Radev
2023	A	`conf`	Meta-Uncertainty in Bayesian Model Comparison. AISTATS Marvin Schmitt, Stefan T. Radev, Paul-Christian Bürkner
2023	J	`jnl`	Sensitivity-Aware Amortized Bayesian Inference. CoRR Lasse Elsemüller, Hans Olischläger, Marvin Schmitt, Paul-Christian Bürkner, Ullrich Köthe, Stefan T. Radev
2023	J	`jnl`	Towards Context-Aware Domain Generalization: Representing Environments with Permutation-Invariant Networks. CoRR Jens Müller, Lars Kühmichel, Martin Rohbeck, Stefan T. Radev, Ullrich Köthe
2022	J	`jnl`	BayesFlow: Learning Complex Stochastic Models With Invertible Neural Networks. IEEE Trans. Neural Networks Learn. Syst. Stefan T. Radev, Ulf K. Mertens, Andreas Voss, Lynton Ardizzone, Ullrich Köthe
2022	J	`jnl`	Meta-Uncertainty in Bayesian Model Comparison. CoRR Marvin Schmitt, Stefan T. Radev, Paul-Christian Bürkner
2021	J	`jnl`	BayesFlow can reliably detect Model Misspecification and Posterior Errors in Amortized Bayesian Inference. CoRR Marvin Schmitt, Paul-Christian Bürkner, Ullrich Köthe, Stefan T. Radev
2021	—	`—`	Deep Learning Architectures for Amortized Bayesian Inference in Cognitive Modeling. Stefan T. Radev
2021	J	`jnl`	OutbreakFlow: Model-based Bayesian inference of disease outbreak dynamics with invertible neural networks and its application to the COVID-19 pandemics in Germany. PLoS Comput. Biol. Stefan T. Radev, Frederik Graw, Simiao Chen, Nico T. Mutters, Vanessa Eichel, Till Bärnighausen, Ullrich Köthe
2020	J	`jnl`	Amortized Bayesian Inference for Models of Cognition. CoRR Stefan T. Radev, Andreas Voss, Eva Marie Wieschen, Paul-Christian Bürkner
2020	J	`jnl`	Amortized Bayesian model comparison with evidential deep learning. CoRR Stefan T. Radev, Marco D'Alessandro, Paul-Christian Bürkner, Ulf K. Mertens, Andreas Voss, Ullrich Köthe
2020	J	`jnl`	BayesFlow: Learning complex stochastic models with invertible neural networks. CoRR Stefan T. Radev, Ulf K. Mertens, Andreas Voss, Lynton Ardizzone, Ullrich Köthe
2020	J	`jnl`	Model-based Bayesian inference of disease outbreak dynamics with invertible neural networks. CoRR Stefan T. Radev, Frederik Graw, Simiao Chen, Nico T. Mutters, Vanessa Eichel, Till Bärnighausen, Ullrich Köthe