| Flownet: Learning optical flow with convolutional networks A Dosovitskiy, P Fischer, E Ilg, P Hausser, C Hazirbas, V Golkov, ... Proceedings of the IEEE international conference on computer vision, 2758-2766, 2015 | 3761* | 2015 |
| A large dataset to train convolutional networks for disparity, optical flow, and scene flow estimation N Mayer, E Ilg, P Hausser, P Fischer, D Cremers, A Dosovitskiy, T Brox Proceedings of the IEEE conference on computer vision and pattern …, 2016 | 2070 | 2016 |
| Associative Domain Adaptation P Haeusser, T Frerix, A Mordvintsev, D Cremers In IEEE International Conference on Computer Vision (ICCV), 2017 | 247 | 2017 |
| Purcell-enhanced single-photon emission from nitrogen-vacancy centers coupled to a tunable microcavity H Kaupp, T Hümmer, M Mader, B Schlederer, J Benedikter, P Haeusser, ... Physical Review Applied 6 (5), 054010, 2016 | 178* | 2016 |
| Learning by Association - A versatile semi-supervised training method for neural networks P Häusser, A Mordvintsev, D Cremers IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017 | 127 | 2017 |
| Associative Deep Clustering: Training a Classification Network with no Labels P Haeusser, J Plapp, V Golkov, E Aljalbout, D Cremers Proc. of the German Conference on Pattern Recognition (GCPR), 2018 | 107 | 2018 |
| Better text understanding through image-to-text transfer K Kurach, S Gelly, M Jastrzebski, P Haeusser, O Teytaud, D Vincent, ... arXiv preprint arXiv:1705.08386, 2017 | 8 | 2017 |
| Functional electrographic flow patterns in patients with persistent atrial fibrillation predict outcome of catheter ablation T Szili‐Torok, Z Kis, R Bhagwandien, S Wijchers, SC Yap, M Hoogendijk, ... Journal of Cardiovascular Electrophysiology 32 (8), 2148-2158, 2021 | 5 | 2021 |
| Golkov,“ A Dosovitskiy, P Fischer, E Ilg, P Häusser, C Hazirbas FlowNet: Learning Optical Flow with Convolutional Networks,” in ICCV 2, 2015 | 3 | 2015 |
| Systems, devices, components and methods for detecting the locations of sources of cardiac rhythm disorders in a patient's heart P Haeusser, P Ruppersberg US Patent 11,484,239, 2022 | 2 | 2022 |
| Semi-supervised training of neural networks P Haeusser, A Mordvintsev US Patent 11,443,170, 2022 | 2 | 2022 |
| Learning by association P Häusser Technische Universität München, 2018 | 2 | 2018 |
| Systems, devices, components and methods for detecting the locations of sources of cardiac rhythm disorders in a patient's heart P Haeusser, P Ruppersberg US Patent 11,389,102, 2022 | 1 | 2022 |
| Methods, Systems, Devices, and Components for Visualizing Electrographic Flow (EGF) DE Luksic, P Haeusser, P Ruppersberg US Patent App. 16/918,588, 2021 | 1 | 2021 |
| Electrographic flow mapping for atrial fibrillation: theoretical basis and preliminary observations DE Haines, MH Kong, P Ruppersberg, P Haeusser, B Avitall, TS Torok, ... Journal of Interventional Cardiac Electrophysiology, 1-14, 2022 | | 2022 |
| Systems, Devices, Components and Methods for Detecting the Locations of Sources of Cardiac Rhythm Disorders in a Patient's Heart Using Body Surface Electrodes and/or Cardiac … P Haeusser, P Ruppersberg, MHSM Kong, JV Koblish US Patent App. 17/499,807, 2022 | | 2022 |
| Use of a neural network to generate a whole atrium 3D reconstruction of electrographic flow and basket catheter geometry from biosignals alone R Gagyi, T Szili-Torok, A Grund, K Ahapov, P Ruppersberg, M Kong, ... Europace 24 (Supplement_1), euac053. 598, 2022 | | 2022 |
| PO-675-02 USE OF A NEURAL NETWORK TO GENERATE A WHOLE ATRIUM 3D RECONSTRUCTION OF ELECTROGRAPHIC FLOW AND BASKET CATHETER GEOMETRY FROM BIOSIGNALS ALONE R Gagyi, T Szili-Torok, A Grund, K Ahapov, P Ruppersberg, MH Kong, ... Heart Rhythm 19 (5), S339-S340, 2022 | | 2022 |
| Electrographic Flow Mapping for Persistent Atrial Fibrillation: Theoretical Basis and Preliminary Observations D Haines, MH Kong, P Ruppersberg, P Haeusser, B Avitall, T Szili-Torok, ... | | 2022 |
| Systems, Devices, Components and Methods for Detecting the Locations of Sources of Cardiac Rhythm Disorders in a Patient's Heart and Generating an Estimate or Probability of … P Ruppersberg, P Haeusser, MHSM Kong, DE Luksic, KS Ahapov US Patent App. 17/331,576, 2021 | | 2021 |
Daniel CremersTechnical University of MunichVerified email at tum.de
