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Philip Haeusser
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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
4750*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
27442016
Associative Domain Adaptation
P Haeusser, T Frerix, A Mordvintsev, D Cremers
In IEEE International Conference on Computer Vision (ICCV), 2017
2872017
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
204*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
1432017
Associative deep clustering: Training a classification network with no labels
P Haeusser, J Plapp, V Golkov, E Aljalbout, D Cremers
Pattern Recognition: 40th German Conference, GCPR 2018, Stuttgart, Germany …, 2019
1312019
Smagt P. vd, Cremers D., and Brox T.,“
A Dosovitskiy, P Fischer, E Ilg, P Häusser, C Hazırbaş, V Golkov
Flownet: Learning optical flow with convolutional networks,” in 2015 IEEE …, 2015
182015
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
112021
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
92017
Electrographic flow mapping for atrial fibrillation: theoretical basis and preliminary observations
DE Haines, MH Kong, P Ruppersberg, P Haeusser, B Avitall, T Szili-Torok, ...
Journal of Interventional Cardiac Electrophysiology 66 (4), 1015-1028, 2023
72023
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
52022
Methods, systems, devices, and components for visualizing electrographic flow (EGF)
DE Lukŝic, P Haeusser, P Ruppersberg
US Patent 11,672,465, 2023
32023
Golkov,“
A Dosovitskiy, P Fischer, E Ilg, P Häusser, C Hazirbas
FlowNet: Learning Optical Flow with Convolutional Networks,” in ICCV 2, 2015
32015
Learning by association
P Häusser
Technische Universität München, 2018
22018
Systems, Devices, Components and Methods for Electroanatomical Mapping of the Heart Using 3D Reconstructions Derived from Biosignals
AT Grund, SM Denner, DE Luksic, P Haeusser, P Ruppersberg, ...
US Patent App. 18/125,630, 2023
2023
PO-02-189 ATRIAL ARRHYTHMIA PREDICTION USING ELECTROGRAPHIC FLOW MAPPING METRICS
JD Hummel, S Castellano, P Haeusser, MH Kong
Heart Rhythm 20 (5), S304, 2023
2023
Methods, Systems, Devices, and Components for Extracting Atrial Signals from QRS and QRST Complexes
L Tenbrink, P Haeusser, P Ruppersberg
US Patent App. 17/831,249, 2023
2023
Systems, Devices, Components and Methods for Detecting the Locations of Sources of Cardiac Rhythm Disorders in a Patient's Heart Using Improved Electrographic Flow (EGF) Methods
P Haeusser, P Ruppersberg, C Dinh
US Patent App. 17/571,496, 2022
2022
Biosignal-Based Intracardiac Navigation Systems, Devices, Components and Methods
SM Denner, P Haeusser, P Ruppersberg, DE Luksic, AT Grund
US Patent App. 17/863,246, 2022
2022
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
2022
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