Nadja Klein - RankMe

55 papers A 3Journal 45Unranked 7

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Depth as Prior Knowledge for Object Detection. CoRR Moussa Kassem Sbeyti, Nadja Klein
2026	J	`jnl`	Scalable Learning of Multivariate Distributions via Coresets. CoRR Zeyu Ding, Katja Ickstadt, Nadja Klein, Alexander Munteanu, Simon Omlor
2026	J	`jnl`	Semi-structured multi-state delinquency model for mortgage default. CoRR Victor Medina-Olivares, Wangzhen Xia, Stefan Lessmann, Nadja Klein
2025	J	`jnl`	Amortized Variational Inference for Partial-Label Learning: A Probabilistic Approach to Label Disambiguation. CoRR Tobias Fuchs, Nadja Klein
2025	J	`jnl`	Anisotropic multidimensional smoothing using Bayesian tensor product P-splines. Stat. Comput. Paul Bach, Nadja Klein
2025	J	`jnl`	Bayesian Regularized Regression Copula Processes for Multivariate Responses. J. Comput. Graph. Stat. Nadja Klein, Michael Stanley Smith, Ryan A. Chisholm, David J. Nott
2025	J	`jnl`	Beware of "Explanations" of AI. CoRR David Martens, Galit Shmueli, Theodoros Evgeniou, Kevin Bauer, Christian Janiesch, Stefan Feuerriegel, Sebastian Gabel, Sofie Goethals, Travis Greene, Nadja Klein, Mathias Kraus, Niklas Kühl, Claudia Perlich, Wouter Verbeke, Alona Zharova, Patrick Zschech, Foster J. Provost
2025	J	`jnl`	Boosting Causal Additive Models. J. Mach. Learn. Res. Maximilian Kertel, Nadja Klein
2025	J	`jnl`	Building Blocks for Robust and Effective Semi-Supervised Real-World Object Detection. CoRR Moussa Kassem Sbeyti, Nadja Klein, Azarm Nowzad, Fikret Sivrikaya, Sahin Albayrak
2025	J	`jnl`	Building Blocks for Robust and Effective Semi-Supervised Real-World Object Detection. Trans. Mach. Learn. Res. Moussa Kassem Sbeyti, Nadja Klein, Azarm Nowzad, Fikret Sivrikaya, Sahin Albayrak
2025	—	`conf`	Closing the Loop: Motion Prediction Models Beyond Open-Loop Benchmarks. ITSC Mohamed-Khalil Bouzidi, Christian Schlauch, Nicole Scheuerer, Yue Yao, Nadja Klein, Daniel Göhring, Jörg Reichardt
2025	J	`jnl`	Closing the Loop: Motion Prediction Models beyond Open-Loop Benchmarks. CoRR Mohamed-Khalil Bouzidi, Christian Schlauch, Nicole Scheuerer, Yue Yao, Nadja Klein, Daniel Göhring, Jörg Reichardt
2025	J	`jnl`	Density regression via Dirichlet process mixtures of normal structured additive regression models. Stat. Comput. María Xosé Rodríguez-Álvarez, Vanda Inácio, Nadja Klein
2025	J	`jnl`	Generative AI for Autonomous Driving: A Review. CoRR Katharina Winter, Abhishek Vivekanandan, Rupert Polley, Yinzhe Shen, Christian Schlauch, Mohamed-Khalil Bouzidi, Bojan Derajic, Natalie Grabowsky, Annajoyce Mariani, Dennis Rochau, Giovanni Lucente, Harsh Yadav, Firas Mualla, Adam Molin, Sebastian Bernhard, Christian Wirth, Ömer Sahin Tas, Nadja Klein, Fabian B. Flohr, Hanno Gottschalk
2025	—	`conf`	MultiFlags: A Probabilistic Framework for Article-Based Size Advice in Fashion E-Commerce. IC3K (KDIR) Matthias Späth, Andrea Nestler, Henry Böddeker, Leonidas Lefakis, Yevgeniy Puzikov, Rodrigo Weffer, Nour Karessli, Nadja Klein, Reza Shirvany
2025	J	`jnl`	Scalable Estimation for Structured Additive Distributional Regression. J. Comput. Graph. Stat. Nikolaus Umlauf, Johannes Seiler, Mattias Wetscher, Thorsten Simon, Stefan Lang, Nadja Klein
2025	J	`jnl`	Streamlining the Development of Active Learning Methods in Real-World Object Detection. CoRR Moussa Kassem Sbeyti, Nadja Klein, Michelle Karg, Christian Wirth, Sahin Albayrak
2025	J	`jnl`	Truly Multivariate Structured Additive Distributional Regression. J. Comput. Graph. Stat. Lucas Kock, Nadja Klein
2025	J	`jnl`	Uncertainty-Aware Trajectory Prediction via Rule-Regularized Heteroscedastic Deep Classification. CoRR Kumar Manas, Christian Schlauch, Adrian Paschke, Christian Wirth, Nadja Klein
2025	A	`conf`	WeedsGalore: A Multispectral and Multitemporal UAV-Based Dataset for Crop and Weed Segmentation in Agricultural Maize Fields. WACV Ekin Celikkan, Timo Kunzmann, Yertay Yeskaliyev, Sibylle Itzerott, Nadja Klein, Martin Herold
2025	J	`jnl`	WeedsGalore: A Multispectral and Multitemporal UAV-based Dataset for Crop and Weed Segmentation in Agricultural Maize Fields. CoRR Ekin Celikkan, Timo Kunzmann, Yertay Yeskaliyev, Sibylle Itzerott, Nadja Klein, Martin Herold
2024	J	`jnl`	Boosting Causal Additive Models. CoRR Maximilian Kertel, Nadja Klein
2024	A	`conf`	Cost-Sensitive Uncertainty-Based Failure Recognition for Object Detection. UAI Moussa Kassem Sbeyti, Michelle Karg, Christian Wirth, Nadja Klein, Sahin Albayrak
2024	J	`jnl`	Cost-Sensitive Uncertainty-Based Failure Recognition for Object Detection. CoRR Moussa Kassem Sbeyti, Michelle Karg, Christian Wirth, Nadja Klein, Sahin Albayrak
2024	—	`conf`	Dropout Regularization in Extended Generalized Linear Models Based on Double Exponential Families. ECML/PKDD (6) Benedikt Lütke Schwienhorst, Lucas Kock, Nadja Klein, David J. Nott
2024	J	`jnl`	From Counting Stations to City-Wide Estimates: Data-Driven Bicycle Volume Extrapolation. CoRR Silke K. Kaiser, Nadja Klein, Lynn H. Kaack
2024	A	`conf`	Informed Spectral Normalized Gaussian Processes for Trajectory Prediction. ECAI Christian Schlauch, Christian Wirth, Nadja Klein
2024	J	`jnl`	Informed Spectral Normalized Gaussian Processes for Trajectory Prediction. CoRR Christian Schlauch, Christian Wirth, Nadja Klein
2024	—	`conf`	Investigating Calibration and Corruption Robustness of Post-hoc Pruned Perception CNNs: An Image Classification Benchmark Study. CVPR Workshops Pallavi Mitra, Gesina Schwalbe, Nadja Klein
2024	J	`jnl`	Investigating Calibration and Corruption Robustness of Post-hoc Pruned Perception CNNs: An Image Classification Benchmark Study. CoRR Pallavi Mitra, Gesina Schwalbe, Nadja Klein
2024	—	`conf`	Sparse Explanations of Neural Networks Using Pruned Layer-Wise Relevance Propagation. ECML/PKDD (4) Paulo Yanez Sarmiento, Simon Witzke, Nadja Klein, Bernhard Y. Renard
2024	J	`jnl`	Sparse Explanations of Neural Networks Using Pruned Layer-Wise Relevance Propagation. CoRR Paulo Yanez Sarmiento, Simon Witzke, Nadja Klein, Bernhard Y. Renard
2024	J	`jnl`	The Deep Promotion Time Cure Model. IEEE Trans. Neural Networks Learn. Syst. Victor Medina-Olivares, Stefan Lessmann, Nadja Klein
2023	J	`jnl`	Correction to : Variational inference and sparsity in high-dimensional deep Gaussian mixture models. Stat. Comput. Lucas Kock, Nadja Klein, David J. Nott
2023	J	`jnl`	Dropout Regularization in Extended Generalized Linear Models based on Double Exponential Families. CoRR Benedikt Lütke Schwienhorst, Lucas Kock, David J. Nott, Nadja Klein
2023	—	`conf`	Informed Priors for Knowledge Integration in Trajectory Prediction. ECML/PKDD (5) Christian Schlauch, Christian Wirth, Nadja Klein
2023	J	`jnl`	Learning Causal Graphs in Manufacturing Domains Using Structural Equation Models. Int. J. Semantic Comput. Maximilian Kertel, Stefan Harmeling, Markus Pauly, Nadja Klein
2023	—	`conf`	Semantic Segmentation of Crops and Weeds with Probabilistic Modeling and Uncertainty Quantification. ICCV (Workshops) Ekin Celikkan, Mohammadmehdi Saberioon, Martin Herold, Nadja Klein
2023	J	`jnl`	The Deep Promotion Time Cure Model. CoRR Victor Medina-Olivares, Stefan Lessmann, Nadja Klein
2023	J	`jnl`	deepregression: A Flexible Neural Network Framework for Semi-Structured Deep Distributional Regression. J. Stat. Softw. David Rügamer, Chris Kolb, Cornelius Fritz, Florian Pfisterer, Philipp Kopper, Bernd Bischl, Ruolin Shen, Christina Bukas, Lisa Barros de Andrade e Sousa, Dominik Thalmeier, Philipp F. M. Baumann, Lucas Kook, Nadja Klein, Christian L. Müller
2022	J	`jnl`	A non-stationary model for spatially dependent circular response data based on wrapped Gaussian processes. Stat. Comput. Isa Marques, Thomas Kneib, Nadja Klein
2022	J	`jnl`	Correcting for sample selection bias in Bayesian distributional regression models. Comput. Stat. Data Anal. Paul F. V. Wiemann, Nadja Klein, Thomas Kneib
2022	J	`jnl`	Informed Priors for Knowledge Integration in Trajectory Prediction. CoRR Christian Schlauch, Nadja Klein, Christian Wirth
2022	J	`jnl`	Using Background Knowledge from Preceding Studies for Building a Random Forest Prediction Model: A Plasmode Simulation Study. Entropy Lorena Hafermann, Nadja Klein, Géraldine Rauch, Michael Kammer, Georg Heinze
2022	J	`jnl`	Variational inference and sparsity in high-dimensional deep Gaussian mixture models. Stat. Comput. Lucas Kock, Nadja Klein, David J. Nott
2021	J	`jnl`	Assessment and Adjustment of Approximate Inference Algorithms Using the Law of Total Variance. J. Comput. Graph. Stat. Xuejun Yu, David J. Nott, Minh-Ngoc Tran, Nadja Klein
2021	J	`jnl`	Marginally Calibrated Deep Distributional Regression. J. Comput. Graph. Stat. Nadja Klein, David J. Nott, Michael Stanley Smith
2021	J	`jnl`	Marginally calibrated response distributions for end-to-end learning in autonomous driving. CoRR Clara Hoffmann, Nadja Klein
2021	J	`jnl`	bamlss: A Lego Toolbox for Flexible Bayesian Regression (and Beyond). J. Stat. Softw. Nikolaus Umlauf, Nadja Klein, Thorsten Simon, Achim Zeileis
2021	J	`jnl`	deepregression: a Flexible Neural Network Framework for Semi-Structured Deep Distributional Regression. CoRR David Rügamer, Ruolin Shen, Christina Bukas, Lisa Barros de Andrade e Sousa, Dominik Thalmeier, Nadja Klein, Chris Kolb, Florian Pfisterer, Philipp Kopper, Bernd Bischl, Christian L. Müller
2020	J	`jnl`	A Unifying Network Architecture for Semi-Structured Deep Distributional Learning. CoRR David Rügamer, Chris Kolb, Nadja Klein
2019	J	`jnl`	Multivariate effect priors in bivariate semiparametric recursive Gaussian models. Comput. Stat. Data Anal. Hauke Thaden, Nadja Klein, Thomas Kneib
2019	J	`jnl`	bamlss: A Lego Toolbox for Flexible Bayesian Regression (and Beyond). CoRR Nikolaus Umlauf, Nadja Klein, Thorsten Simon, Achim Zeileis
2018	J	`jnl`	Studying the occurrence and burnt area of wildfires using zero-one-inflated structured additive beta regression. Environ. Model. Softw. Laura Ríos-Pena, Thomas Kneib, Carmen Cadarso-Suárez, Nadja Klein, Manuel Marey-Pérez
2016	J	`jnl`	Simultaneous inference in structured additive conditional copula regression models: a unifying Bayesian approach. Stat. Comput. Nadja Klein, Thomas Kneib