Search Results - "Lagemann, Kai"

Deep recurrent optical flow learning for particle image velocimetry data by Lagemann, Christian, Lagemann, Kai, Mukherjee, Sach, Schröder, Wolfgang

“…A wide range of problems in applied physics and engineering involve learning physical displacement fields from data. In this paper we propose a deep neural…”
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Challenges of deep unsupervised optical flow estimation for particle-image velocimetry data by Lagemann, Christian, Lagemann, Kai, Mukherjee, Sach, Schröder, Wolfgang

“…In recent years, several algorithms have been proposed that leverage deep learning techniques within the analysis workflow of particle-image velocimetry (PIV)…”
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Deep learning of causal structures in high dimensions under data limitations by Lagemann, Kai, Lagemann, Christian, Taschler, Bernd, Mukherjee, Sach

“…Causal learning is a key challenge in scientific artificial intelligence as it allows researchers to go beyond purely correlative or predictive analyses…”
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Learning Latent Dynamics via Invariant Decomposition and (Spatio-)Temporal Transformers by Lagemann, Kai, Lagemann, Christian, Mukherjee, Sach

“…We propose a method for learning dynamical systems from high-dimensional empirical data that combines variational autoencoders and (spatio-)temporal attention…”
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Deep Learning of Causal Structures in High Dimensions by Lagemann, Kai, Lagemann, Christian, Taschler, Bernd, Mukherjee, Sach

“…Recent years have seen rapid progress at the intersection between causality and machine learning. Motivated by scientific applications involving…”
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