Oliver Dürr - RankMe

31 papers A 2B 2Journal 20Unranked 6

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	AutoStan: Autonomous Bayesian Model Improvement via Predictive Feedback. CoRR Oliver Dürr
2025	J	`jnl`	Assessing deep learning: a work program for the humanities in the age of artificial intelligence. AI Ethics Jan Segessenmann, Thilo Stadelmann, Andrew Davison, Oliver Dürr
2025	—	`conf`	Interpretable Neural Causal Models with TRAM-DAGs. CLeaR Beate Sick, Oliver Dürr
2025	J	`jnl`	Interpretable Neural Causal Models with TRAM-DAGs. CoRR Beate Sick, Oliver Dürr
2025	A	`conf`	Paths and Ambient Spaces in Neural Loss Landscapes. AISTATS Daniel Dold, Julius Kobialka, Nicolai Palm, Emanuel Sommer, David Rügamer, Oliver Dürr
2025	J	`jnl`	Paths and Ambient Spaces in Neural Loss Landscapes. CoRR Daniel Dold, Julius Kobialka, Nicolai Palm, Emanuel Sommer, David Rügamer, Oliver Dürr
2024	A	`conf`	Bayesian Semi-structured Subspace Inference. AISTATS Daniel Dold, David Rügamer, Beate Sick, Oliver Dürr
2024	J	`jnl`	Bayesian Semi-structured Subspace Inference. CoRR Daniel Dold, David Rügamer, Beate Sick, Oliver Dürr
2024	J	`jnl`	Estimating Conditional Distributions with Neural Networks Using J. Stat. Softw. Lucas Kook, Philipp F. M. Baumann, Oliver Dürr, Beate Sick, David Rügamer
2023	J	`jnl`	Bayesian Calibration of MEMS Accelerometers. CoRR Oliver Dürr, Po-Yu Fan, Zong-Xian Yin
2023	J	`jnl`	Short-Term Density Forecasting of Low-Voltage Load Using Bernstein-Polynomial Normalizing Flows. IEEE Trans. Smart Grid Marcel Arpogaus, Marcus Voss, Beate Sick, Mark Nigge-Uricher, Oliver Dürr
2023	J	`jnl`	Single-shot Bayesian approximation for neural networks. CoRR Kai Brach, Beate Sick, Oliver Dürr
2022	J	`jnl`	Bernstein Flows for Flexible Posteriors in Variational Bayes. CoRR Oliver Dürr, Stephan Hörling, Daniel Dold, Ivonne Kovylov, Beate Sick
2022	J	`jnl`	Deep and interpretable regression models for ordinal outcomes. Pattern Recognit. Lucas Kook, Lisa Herzog, Torsten Hothorn, Oliver Dürr, Beate Sick
2022	J	`jnl`	Short-Term Density Forecasting of Low-Voltage Load using Bernstein-Polynomial Normalizing Flows. CoRR Marcel Arpogaus, Marcus Voss, Beate Sick, Mark Nigge-Uricher, Oliver Dürr
2021	J	`jnl`	Transformation Models for Flexible Posteriors in Variational Bayes. CoRR Sefan Hörtling, Daniel Dold, Oliver Dürr, Beate Sick
2020	B	`conf`	Deep transformation models: Tackling complex regression problems with neural network based transformation models. ICPR Beate Sick, Torsten Hothorn, Oliver Dürr
2020	J	`jnl`	Deep transformation models: Tackling complex regression problems with neural network based transformation models. CoRR Beate Sick, Torsten Hothorn, Oliver Dürr
2020	J	`jnl`	Integrating uncertainty in deep neural networks for MRI based stroke analysis. CoRR Lisa Herzog, Elvis Murina, Oliver Dürr, Susanne Wegener, Beate Sick
2020	J	`jnl`	Integrating uncertainty in deep neural networks for MRI based stroke analysis. Medical Image Anal. Lisa Herzog, Elvis Murina, Oliver Dürr, Susanne Wegener, Beate Sick
2020	J	`jnl`	Ordinal Neural Network Transformation Models: Deep and interpretable regression models for ordinal outcomes. CoRR Lucas Kook, Lisa Herzog, Torsten Hothorn, Oliver Dürr, Beate Sick
2020	J	`jnl`	Single Shot MC Dropout Approximation. CoRR Kai Brach, Beate Sick, Oliver Dürr
2019	—	`ch.`	Beyond ImageNet: Deep Learning in Industrial Practice. Applied Data Science Thilo Stadelmann, Vasily Tolkachev, Beate Sick, Jan Stampfli, Oliver Dürr
2019	J	`jnl`	Bone erosion scoring for rheumatoid arthritis with deep convolutional neural networks. Comput. Electr. Eng. Janick Rohrbach, Tobias Reinhard, Beate Sick, Oliver Dürr
2018	—	`conf`	Capturing Suprasegmental Features of a Voice with RNNs for Improved Speaker Clustering. ANNPR Thilo Stadelmann, Sebastian Glinski-Haefeli, Patrick Gerber, Oliver Dürr
2018	—	`conf`	Learning Neural Models for End-to-End Clustering. ANNPR Benjamin Bruno Meier, Ismail Elezi, Mohammadreza Amirian, Oliver Dürr, Thilo Stadelmann
2015	—	`conf`	Deep Learning on a Raspberry Pi for Real Time Face Recognition. Eurographics (Posters) Oliver Dürr, Yves Pauchard, Diego Browarnik, Rebekka Axthelm, Martin Loeser
2014	—	`conf`	JOINT_FORCES: Unite Competing Sentiment Classifiers with Random Forest. SemEval@COLING Oliver Dürr, Fatih Uzdilli, Mark Cieliebak
2014	B	`conf`	Meta-Classifiers Easily Improve Commercial Sentiment Detection Tools. LREC Mark Cieliebak, Oliver Dürr, Fatih Uzdilli
2013	—	`conf`	Potential and Limitations of Commercial Sentiment Detection Tools. ESSEM@AI*IA Mark Cieliebak, Oliver Dürr, Fatih Uzdilli
2012	J	`jnl`	Using Community Structure for Complex Network Layout CoRR Oliver Dürr, Arnd Brandenburg