Max-Heinrich Laves

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All published works

Action	Title	Year	Authors
+ PDF Chat	Unsupervised anomaly detection in 3D brain MRI using deep learning with multi-task brain age prediction	2022	Marcel Bengs Finn Behrendt Max-Heinrich Laves Julia Krüger Roland Opfer Alexander Schlaefer
+ PDF Chat	Posterior temperature optimized Bayesian models for inverse problems in medical imaging	2022	Max-Heinrich Laves Malte Tölle Alexander Schlaefer Sandy Engelhardt
+ PDF Chat	Robotic Tissue Sampling for Safe Post-Mortem Biopsy in Infectious Corpses	2022	Maximilian Neidhardt Stefan Gerlach Robin Mieling Max-Heinrich Laves Thorben Weib Martin Gromniak Antonia Fitzek Dustin Möbius Inga Kniep Alexandra Ron
+	Unsupervised Anomaly Detection in 3D Brain MRI using Deep Learning with Multi-Task Brain Age Prediction	2022	Marcel Bengs Finn Behrendt Max-Heinrich Laves Julia Krüger Roland Opfer Alexander Schlaefer
+	Posterior temperature optimized Bayesian models for inverse problems in medical imaging	2022	Max-Heinrich Laves Malte Tölle Alexander Schlaefer Sandy Engelhardt
+	Posterior Temperature Optimization in Variational Inference for Inverse Problems.	2021	Max-Heinrich Laves Malte Tölle Alexander Schlaefer Sandy Engelhardt
+	Cold Posteriors Improve Bayesian Medical Image Post-Processing	2021	Max-Heinrich Laves Malte Tölle Alexander Schlaefer
+	Posterior Temperature Optimization in Variational Inference.	2021	Max-Heinrich Laves Malte Tölle Alexander Schlaefer
+ PDF Chat	Recalibration of Aleatoric and EpistemicRegression Uncertainty in Medical Imaging	2021	Max-Heinrich Laves Sontje Ihler Jacob Friedemann Fast Lüder A. Kahrs Tobias Ortmaier
+	Recalibration of Aleatoric and Epistemic Regression Uncertainty in Medical Imaging.	2021	Max-Heinrich Laves Sontje Ihler Jacob Friedemann Fast Lüder A. Kahrs Tobias Ortmaier
+	Posterior Temperature Optimization in Variational Inference for Inverse Problems	2021	Max-Heinrich Laves Malte Tölle Alexander Schlaefer Sandy Engelhardt
+	Recalibration of Aleatoric and Epistemic Regression Uncertainty in Medical Imaging	2021	Max-Heinrich Laves Sontje Ihler Jacob Friedemann Fast Lüder A. Kahrs Tobias Ortmaier
+	Uncertainty Estimation in Medical Image Denoising with Bayesian Deep Image Prior	2020	Max-Heinrich Laves Malte Tölle Tobias Ortmaier
+	Patient-Specific Domain Adaptation for Fast Optical Flow Based on Teacher-Student Knowledge Transfer.	2020	Sontje Ihler Max-Heinrich Laves Tobias Ortmaier
+	Calibration of Model Uncertainty for Dropout Variational Inference	2020	Max-Heinrich Laves Sontje Ihler Karl-Philipp Kortmann Tobias Ortmaier
+ PDF Chat	Uncertainty Estimation in Medical Image Denoising with Bayesian Deep Image Prior	2020	Max-Heinrich Laves Malte Tölle Tobias Ortmaier
+	Uncertainty Estimation in Medical Image Denoising with Bayesian Deep Image Prior	2020	Max-Heinrich Laves Malte Tölle Tobias Ortmaier
+	Patient-Specific Domain Adaptation for Fast Optical Flow Based on Teacher-Student Knowledge Transfer	2020	Sontje Ihler Max-Heinrich Laves Tobias Ortmaier
+	Uncertainty Quantification in Computer-Aided Diagnosis: Make Your Model say "I don't know" for Ambiguous Cases	2019	Max-Heinrich Laves Sontje Ihler Tobias Ortmaier
+	Deformable Medical Image Registration Using a Randomly-Initialized CNN as Regularization Prior	2019	Max-Heinrich Laves Sontje Ihler Tobias Ortmaier
+ PDF Chat	Semantic denoising autoencoders for retinal optical coherence tomography	2019	Max-Heinrich Laves Sontje Ihler Lüder A. Kahrs Tobias Ortmaier
+	Semantic denoising autoencoders for retinal optical coherence tomography	2019	Max-Heinrich Laves Sontje Ihler Lüder A. Kahrs Tobias Ortmaier
+ PDF Chat	Deep-learning-based 2.5D flow field estimation for maximum intensity projections of 4D optical coherence tomography	2019	Max-Heinrich Laves Lüder A. Kahrs Tobias Ortmaier Sontje Ihler
+	Endoscopic vs. volumetric OCT imaging of mastoid bone structure for pose estimation in minimally invasive cochlear implant surgery.	2019	Max-Heinrich Laves Sarah Latus Jan Bergmeier Tobias Ortmaier Lüder A. Kahrs Alexander Schlaefer
+ PDF Chat	A dataset of laryngeal endoscopic images with comparative study on convolution neural network-based semantic segmentation	2019	Max-Heinrich Laves Jens Bicker Lüder A. Kahrs Tobias Ortmaier
+	Retinal OCT disease classification with variational autoencoder regularization	2019	Max-Heinrich Laves Sontje Ihler Lüder A. Kahrs Tobias Ortmaier
+	Well-calibrated Model Uncertainty with Temperature Scaling for Dropout Variational Inference	2019	Max-Heinrich Laves Sontje Ihler Karl-Philipp Kortmann Tobias Ortmaier
+	Semantic denoising autoencoders for retinal optical coherence tomography	2019	Max-Heinrich Laves Sontje Ihler Lüder A. Kahrs Tobias Ortmaier
+	Deformable Medical Image Registration Using a Randomly-Initialized CNN as Regularization Prior	2019	Max-Heinrich Laves Sontje Ihler Tobias Ortmaier
+	Uncertainty Quantification in Computer-Aided Diagnosis: Make Your Model say "I don't know" for Ambiguous Cases	2019	Max-Heinrich Laves Sontje Ihler Tobias Ortmaier
+	Endoscopic vs. volumetric OCT imaging of mastoid bone structure for pose estimation in minimally invasive cochlear implant surgery	2019	Max-Heinrich Laves Sarah Latus Jan Bergmeier Tobias Ortmaier Lüder A. Kahrs Alexander Schlaefer
+	Deep learning based 2.5D flow field estimation for maximum intensity projections of 4D optical coherence tomography	2018	Max-Heinrich Laves Lüder A. Kahrs Tobias Ortmaier
+	A Dataset of Laryngeal Endoscopic Images with Comparative Study on Convolution Neural Network Based Semantic Segmentation	2018	Max-Heinrich Laves Jens Bicker Lüder A. Kahrs Tobias Ortmaier
+	Deep learning based 2.5D flow field estimation for maximum intensity projections of 4D optical coherence tomography	2018	Max-Heinrich Laves Lüder A. Kahrs Tobias Ortmaier
+	A Dataset of Laryngeal Endoscopic Images with Comparative Study on Convolution Neural Network Based Semantic Segmentation	2018	Max-Heinrich Laves Jens Bicker Lüder A. Kahrs Tobias Ortmaier

Common Coauthors

Coauthor	Papers Together
Tobias Ortmaier	26
Sontje Ihler	16
Lüder A. Kahrs	15
Alexander Schlaefer	11
Malte Tölle	9
Sandy Engelhardt	4
Jacob Friedemann Fast	3
Jens Bicker	2
Karl-Philipp Kortmann	2
Jan Bergmeier	2
Roland Opfer	2
Sarah Latus	2
Marcel Bengs	2
Finn Behrendt	2
Jens Bicker	1
Maximilian Neidhardt	1
Julia Krüger	1
Martin Gromniak	1
Julia Krüger	1
Thorben Weib	1
Antonia Fitzek	1
Robin Mieling	1
Alexandra Ron	1
Dustin Möbius	1
Julia Schädler	1
Klaus Püschel	1
Stefan Gerlach	1
Benjamin Ondruschka	1
Inga Kniep	1
Axel Heinemann	1

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+	Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning	2015	Yarin Gal Zoubin Ghahramani	8
+	What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?	2017	Alex Kendall Yarin Gal	6
+ PDF Chat	A deep learning approach for pose estimation from volumetric OCT data	2018	Nils Gessert Matthias Schlüter Alexander Schlaefer	5
+ PDF Chat	Deep Residual Learning for Image Recognition	2016	Kaiming He Xiangyu Zhang Shaoqing Ren Jian Sun	5
+ PDF Chat	Densely Connected Convolutional Networks	2017	Gao Huang Zhuang Liu Laurens van der Maaten Kilian Q. Weinberger	4
+	Pattern Recognition and Machine Learning	2007	Christopher Bishop	4
+ PDF Chat	A Bayesian Perspective on the Deep Image Prior	2019	Zezhou Cheng Matheus Gadelha Subhransu Maji Daniel Sheldon	3
+	Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles	2016	Balaji Lakshminarayanan Alexander Pritzel Charles Blundell	3
+ PDF Chat	Denoising adversarial autoencoders: classifying skin lesions using limited labelled training data	2018	Antonia Creswell Alison Pouplin Anil A. Bharath	3
+ PDF Chat	Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising	2017	Kai Zhang Wangmeng Zuo Yunjin Chen Deyu Meng Lei Zhang	3
+	Accurate Uncertainties for Deep Learning Using Calibrated Regression	2018	Volodymyr Kuleshov Nathan Fenner Stefano Ermon	2
+	Well-calibrated Model Uncertainty with Temperature Scaling for Dropout Variational Inference	2019	Max-Heinrich Laves Sontje Ihler Karl-Philipp Kortmann Tobias Ortmaier	2
+ PDF Chat	On the Applicability of Registration Uncertainty	2019	Jie Luo Alireza Sedghi Karteek Popuri Dana Cobzaş Miaomiao Zhang Frank Preiswerk Matthew Toews Alexandra J. Golby Masashi Sugiyama William M. Wells	2
+ PDF Chat	Automatic kidney segmentation in ultrasound images using subsequent boundary distance regression and pixelwise classification networks	2019	Shi Yin Qinmu Peng Hongming Li Zhengqiang Zhang Xinge You Katherine Fischer Susan L. Furth Gregory E. Tasian Yong Fan	2
+	Bayesian Deep Learning and a Probabilistic Perspective of Generalization	2020	Andrew Gordon Wilson Pavel Izmailov	2
+	Concrete Dropout	2017	Yarin Gal Jiri Hron Alex Kendall	2
+	Computed tomography reconstruction using deep image prior and learned reconstruction methods	2020	Daniel Otero Baguer Johannes Leuschner Maximilian Schmidt	2
+ PDF Chat	Uncertainty in Multitask Learning: Joint Representations for Probabilistic MR-only Radiotherapy Planning	2018	Felix Bragman Ryutaro Tanno Zach Eaton-Rosen Wenqi Li David J. Hawkes Sébastien Ourselin Daniel C. Alexander Jamie R. McClelland M. Jorge Cardoso	2
+ PDF Chat	Medical Image Denoising Using Convolutional Denoising Autoencoders	2016	Lovedeep Gondara	2
+	A Tutorial on Bayesian Optimization	2018	Peter I. Frazier	2
+	Categorical Reparameterization with Gumbel-Softmax	2016	Eric Jang Shixiang Gu Ben Poole	2
+ PDF Chat	Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification	2015	Kaiming He Xiangyu Zhang Shaoqing Ren Jian Sun	2
+ PDF Chat	Fully convolutional networks for semantic segmentation	2015	Jonathan Long Evan Shelhamer Trevor Darrell	2
+ PDF Chat	FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks	2017	Eddy Ilg N. Michael Mayer Tonmoy Saikia Margret Keuper Alexey Dosovitskiy Thomas Brox	2
+ PDF Chat	Real-Time Segmentation of Non-rigid Surgical Tools Based on Deep Learning and Tracking	2017	Luis C. García-Peraza-Herrera Wenqi Li Caspar Gruijthuijsen Alain Devreker George Attilakos Jan Deprest Emmanuel Vander Poorten Danail Stoyanov Tom Vercauteren Sébastien Ourselin	2
+	Calibrating Uncertainties in Object Localization Task	2018	Buu Phan Rick Salay Krzysztof Czarnecki Vahdat Abdelzad Taylor Denouden Sachin Vernekar	2
+	Bayesian Learning via Stochastic Gradient Langevin Dynamics	2011	Max Welling Yee Whye Teh	2
+ PDF Chat	Automatic Classification of Cancerous Tissue in Laserendomicroscopy Images of the Oral Cavity using Deep Learning	2017	Marc Aubreville Christian Knipfer Nicolai Oetter Christian Jaremenko Erik Rodner Joachim Denzler Christopher Bohr Helmut Neumann Florian Stelzle Andreas Maier	2
+ PDF Chat	Bayesian Image Quality Transfer with CNNs: Exploring Uncertainty in dMRI Super-Resolution	2017	Ryutaro Tanno Daniel E. Worrall Aurobrata Ghosh Enrico Kaden Stamatios N. Sotiropoulos Antonio Criminisi Daniel C. Alexander	2
+ PDF Chat	Unsupervised learning of probabilistic diffeomorphic registration for images and surfaces	2019	Adrian V. Dalca Guha Balakrishnan John Guttag Mert R. Sabuncu	2
+	Integrating spatial configuration into heatmap regression based CNNs for landmark localization	2019	Christian Payer Darko Štern Horst Bischof Martin Urschler	2
+	On Calibration of Modern Neural Networks	2017	Chuan Guo Geoff Pleiss Yu Sun Kilian Q. Weinberger	2
+ PDF Chat	Evaluating and Calibrating Uncertainty Prediction in Regression Tasks	2022	Dan Levi Liran Gispan Niv Giladi Ethan Fetaya	2
+	Preconditioned Stochastic Gradient Langevin Dynamics for Deep Neural Networks	2015	Chunyuan Li Changyou Chen David Carlson Lawrence Carin	2
+	Regularizing Neural Networks by Penalizing Confident Output Distributions	2017	Gabriel Pereyra George Tucker Jan Chorowski Łukasz Kaiser Geoffrey E. Hinton	2
+ PDF Chat	The Cityscapes Dataset for Semantic Urban Scene Understanding	2016	Marius Cordts Mohamed Omran Sebastian Ramos Timo Rehfeld Markus Enzweiler Rodrigo Benenson Uwe Franke Stefan Roth Bernt Schiele	2
+ PDF Chat	Convolutional Neural Networks for Medical Image Analysis: Full Training or Fine Tuning?	2016	Nima Tajbakhsh Jae Y. Shin Suryakanth R. Gurudu R. Todd Hurst Christopher B. Kendall Michael B. Gotway Jianming Liang	2
+	Interactive Medical Image Segmentation Using Deep Learning With Image-Specific Fine Tuning	2018	Guotai Wang Wenqi Li María A. Zuluaga Rosalind Pratt Premal A. Patel Michaël Aertsen Tom Doel Anna L. David Jan Deprest Sébastien Ourselin	2
+	ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation	2016	Adam Paszke Abhishek Chaurasia Sangpil Kim Eugenio Culurciello	2
+	EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks	2019	Mingxing Tan Quoc V. Le	2
+ PDF Chat	Semantic denoising autoencoders for retinal optical coherence tomography	2019	Max-Heinrich Laves Sontje Ihler Lüder A. Kahrs Tobias Ortmaier	2
+ PDF Chat	Stochastic Deep Compressive Sensing for the Reconstruction of Diffusion Tensor Cardiac MRI	2018	Jo Schlemper Guang Yang Pedro Ferreira Andrew D. Scott Laura‐Ann McGill Zohya Khalique Margarita Gorodezky Malte Roehl Jennifer Keegan Dudley J. Pennell	2
+	SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation	2017	Vijay Badrinarayanan A. C. Kendall Roberto Cipolla	2
+ PDF Chat	Autoencoders for unsupervised anomaly segmentation in brain MR images: A comparative study	2021	Christoph Baur Stefan Denner Benedikt Wiestler Nassir Navab Shadi Albarqouni	1
+	Bayesian Uncertainty Estimation of Learned Variational MRI Reconstruction	2021	Dominik Narnhofer Alexander Effland Erich Kobler Kerstin Hammernik Florian Knöll Thomas Pock	1
+	Recalibration of Aleatoric and Epistemic Regression Uncertainty in Medical Imaging.	2021	Max-Heinrich Laves Sontje Ihler Jacob Friedemann Fast Lüder A. Kahrs Tobias Ortmaier	1
+ PDF Chat	MADGAN: unsupervised medical anomaly detection GAN using multiple adjacent brain MRI slice reconstruction	2021	Changhee Han Leonardo Rundo Kohei Murao Tomoyuki Noguchi Yuki Shimahara Zoltán Á. Milacski Saori Koshino Evis Sala Hideki Nakayama Shin’ichi Satoh	1
+	What Are Bayesian Neural Network Posteriors Really Like	2021	Pavel Izmailov Sharad Vikram Matthew D. Hoffman Andrew Gordon Wilson	1
+ PDF Chat	Recalibration of Aleatoric and EpistemicRegression Uncertainty in Medical Imaging	2021	Max-Heinrich Laves Sontje Ihler Jacob Friedemann Fast Lüder A. Kahrs Tobias Ortmaier	1
+ PDF Chat	Deep Learning for Medical Anomaly Detection – A Survey	2021	Tharindu Fernando Harshala Gammulle Simon Denman Sridha Sridharan Clinton Fookes	1