Publications
2022
Garrido, Q, Damrich, S, Jäger, A, Cerletti, D, Claassen, M, Najman, L and Hamprecht, F A (2022).
Visualizing hierarchies in scRNA-seq data using a density tree-biased autoencoder.
Bioinformatics. arXiv preprint.
38 (Suppl 1) i316-i324
2021
Milbich, T, Roth, K, Sinha, S, Schmidt, L, Ghassemi, M and Ommer, B (2021).
Characterizing Generalization under Out-Of-Distribution Shifts in Deep Metric Learning.
https://arxiv.org/abs/2107.09562 Pape, C, Remme, R, Wolny, A, Olberg, S, Wolf, S, Cerrone, L, Cortese, M, Klaus, S, Lucic, B, Ullrich, S, Anders-Össwein, M, Wolf, S, Cerikan, B, Neufeldt, C J, Ganter, M, Schnitzler, P, Merle, U, Lusic, M, Boulant, S, Stanifer, M, Bartenschlager, R, Hamprecht, F A, Kreshuk, A, Tischer, C, Kräusslich, H - G, Müller, B and Laketa, V (2021).
Microscopy-based assay for semi-quantitative detection of SARS-CoV-2 specific antibodies in human sera.
BioEssays.
43 Arlt, H, Sui, X, Folger, B, Adams, C, Chen, X, Remme, R, Hamprecht, F A, DiMaio, F, Liao, M, Goodman, J M, Farese, R V and Walther, T C (2021).
Seipin forms a flexible cage at lipid droplet formation sites. bioRxiv
2020
Schnörr, (2020).
Assignment Flows.
Handbook of Variational Methods for Nonlinear Geometric Data. Springer. 235—260.
https://www.springer.com/gp/book/9783030313500 Schilling, H, Gutsche, M, Brock, A, Späth, D, Rother, C and Krispin, K (2020).
Mind the Gap – A Benchmark for Dense Depth Prediction beyond Lidar.
2nd Workshop on Safe Artificial Intelligence for Automated Driving, in conjunction with CVPR 2020 Roth, K, Milbich, T, Sinha, S, Gupta, P, Ommer, B and Cohen, J Paul (2020).
Revisiting Training Strategies and Generalization Performance in Deep Metric Learning.
International Conference on Machine Learning (ICML).
https://arxiv.org/pdf/2002.08473.pdf 2019
Schnörr, (2019).
Assignment Flows.
Variational Methods for Nonlinear Geometric Data and Applications. Springer
Bendinger, A L, Debus, C, Glowa, C, Karger, C P, Peter, J and Storath, M (2019).
Bolus arrival time estimation in dynamic contrast-enhanced magnetic resonance imaging of small animals based on spline models, in press.
Physics in Medicine and Biology.
64 Mackowiak, R, Lenz, P, Ghori, O, Diego, F, Lange, O and Rother, C (2019).
CEREALS - Cost-Effective REgion-based Active Learning for Semantic Segmentation.
British Machine Vision Conference 2018, BMVC 2018 Imle, A, Kumberger, P, Schnellbächer, N D, Fehr, J, Carillo-Bustamente, P, Ales, J, Schmidt, P, Ritter, C, Godinez, W J, Müller, B, Rohr, K, Hamprecht, F A, Schwarz, U S, Graw, F and Fackler, O T (2019).
Experimental and computational analyses reveal that environmental restrictions shape HIV-1 spread in 3D cultures.
Nature Communications.
13;10(1) Imle, A, Kumberger, P, Schnellbächer, N D, Fehr, J, Carillo-Bustamente, P, Ales, J, Schmidt, P, Ritter, C, Godinez, W J, Müller, B, Rohr, K, Hamprecht, F A, Schwarz, U S, Graw, F and Fackler, O T (2019).
Experimental and computational analyses reveal that environmental restrictions shape HIV-1 spread in 3D cultures.
Nature Communications.
13;10(1) Abu Alhaija, H, Mustikovela, S Karthik, Geiger, A and Rother, C (2019).
Geometric Image Synthesis.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).
11366 LNCS 85–100.
https://youtu.be/W2tFCz9xJoU Bengio, Y, Deleu, T, Rahaman, N, Ke, R, Lachapelle, S, Bilaniuk, O, Goyal, A and Pal, C (2019).
A Meta-Transfer Objective for Learning to Disentangle Causal Mechanisms.
arXiv preprint arXiv:1901.10912
Technical Report (871.59 KB) Esposito, M, Hennersperger, C, Göbl, R, Demaret, L, Storath, M, Navab, N, Baust, M and Weinmann, A (2019).
Total variation regularization of pose signals with an application to 3D freehand ultrasound.
IEEE Transactions on Medical Imaging.
38(10) 2245-2258
2018
Ghori, O, Mackowiak, R, Bautista, M, Beuter, N, Drumond, L, Diego, F and Ommer, B (2018).
Learning to Forecast Pedestrian Intention from Pose Dynamics.
Intelligent Vehicles, IEEE, 2018 2017
Behl, A, Hosseini Jafari, O, Mustikovela, S Karthik, Abu Alhaija, H, Rother, C and Geiger, A (2017).
Bounding Boxes, Segmentations and Object Coordinates: How Important is Recognition for 3D Scene Flow Estimation in Autonomous Driving Scenarios?.
Proceedings of the IEEE International Conference on Computer Vision.
2017-Octob 2593–2602
Behl, A, Hosseini Jafari, O, Mustikovela, S Karthik, Abu Alhaija, H, Rother, C and Geiger, A (2017).
Bounding Boxes, Segmentations and Object Coordinates: How Important is Recognition for 3D Scene Flow Estimation in Autonomous Driving Scenarios?.
Proceedings of the IEEE International Conference on Computer Vision.
2017-Octob 2593–2602
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