FlowNet: Learning Optical Flow with Convolutional Networks. - Alexey Dosovitskiy; Philipp Fischer; Eddy Ilg; Philip Häusser; Caner Hazirbas; Vladimir Golkov; Patrick van der Smagt; Daniel Cremers; Thomas Brox (ICCV, 2015)

A Large Dataset to Train Convolutional Networks for Disparity, Optical Flow, and Scene Flow Estimation. - Nikolaus Mayer; Eddy Ilg; Philip Häusser; Philipp Fischer; Daniel Cremers; Alexey Dosovitskiy; Thomas Brox (CVPR, 2016)

Learning by Association - A Versatile Semi-Supervised Training Method for Neural Networks. - Philip Häusser; Alexander Mordvintsev; Daniel Cremers (CVPR, 2017)

Associative Domain Adaptation. - Philip Häusser; Thomas Frerix; Alexander Mordvintsev; Daniel Cremers (ICCV, 2017)

Better Text Understanding Through Image-To-Text Transfer. - Karol Kurach; Sylvain Gelly; Michal Jastrzebski; Philip Häusser; Olivier Teytaud; Damien Vincent; Olivier Bousquet (CoRR, 2017)

Associative Deep Clustering: Training a Classification Network with No Labels. - Philip Häusser; Johannes Plapp; Vladimir Golkov; Elie Aljalbout; Daniel Cremers (GCPR, 2018)

Learning by Association: Strategies for solving computer vision tasks with less labeled data. - Philip Häusser (2018)

Spatio-Temporal Activation Wavefront Reconstruction From Sparsely Sampled Electrograms. - Kostiantyn Ahapov; Peter Ruppersberg; Philip Häusser; Melissa H. Kong; Michael Möller 001 (IEEE Trans. Biomed. Eng., 2025)