| Learning partially known stochastic dynamics with empirical PAC Bayes M Haußmann, S Gerwinn, A Look, B Rakitsch, M Kandemir International Conference on Artificial Intelligence and Statistics, 478-486, 2021 | 20 | 2021 |
| Differential Bayesian Neural Nets A Look, M Kandemir Bayesian Deep Learning Workshop 2019, 2019 | 13 | 2019 |
| Differentiable Implicit Layers A Look, S Doneva, M Kandemir, R Gemulla, J Peters Workshop on machine learning for engineering modeling, simulation and design …, 2020 | 12 | 2020 |
| A system of equations: Mathematics lessons in classical literature VF Ochkov, A Look Journal of Humanistic Mathematics 5 (2), 121-132, 2015 | 10 | 2015 |
| Cheap and Deterministic Inference for Deep State-Space Models of Interacting Dynamical Systems A Look, M Kandemir, B Rakitsch, J Peters Transactions on Machine Learning Research, 2023 | 7 | 2023 |
| A deterministic approximation to neural sdes A Look, M Kandemir, B Rakitsch, J Peters IEEE Transactions on Pattern Analysis and Machine Intelligence 45 (4), 4023-4037, 2022 | 7* | 2022 |
| Building Robust Classifiers with Generative Adversarial Networks for Detecting Cavitation in Hydraulic Turbines. A Look, O Kirschner, S Riedelbauch ICPRAM 2018, 456-462, 2018 | 6 | 2018 |
| Can you text what is happening? integrating pre-trained language encoders into trajectory prediction models for autonomous driving A Keysan, A Look, E Kosman, G Gürsun, J Wagner, Y Yu, B Rakitsch arXiv preprint arXiv:2309.05282, 2023 | 5 | 2023 |
| Cavitation Damage Detection Through Acoustic Emissions A Look, S Riedelbauch, J Necker, A Jung IOP Conference Series: Earth and Environmental Science 405 (1), 012004, 2019 | 4 | 2019 |
| Detection and level estimation of cavitation in hydraulic turbines with convolutional neural networks A Look, O Kirschner, S Riedelbauch, JÖ Necker | 3 | 2018 |
| Sampling-Free Probabilistic Deep State-Space Models A Look, M Kandemir, B Rakitsch, J Peters arXiv preprint arXiv:2309.08256, 2023 | 1 | 2023 |
| Dealing with Limited Access to Data: Comparison of Deep Learning Approaches A Look, S Riedelbauch 2019 International Joint Conference on Neural Networks (IJCNN), 1-8, 2019 | 1* | 2019 |
| Making time-series predictions of a computer-controlled system M Kandemir, S Gerwinn, A Look, B Rakitsch US Patent 11,868,887, 2024 | | 2024 |
| Computer-implemented method for predicting a behavior of agents in a dynamic system with a multiplicity of interacting agents A Look, B Rakitsch, J Peters US Patent App. 18/308,629, 2023 | | 2023 |
| Deterministic Approximations for Deep State-Space Models A Look Technische Universität Darmstadt, 2023 | | 2023 |
| Device and method for training the neural drift network and the neural diffusion network of a neural stochastic differential equation A Look, M Kandemir US Patent App. 17/646,197, 2022 | | 2022 |
| Predicting a state of a computer-controlled entity A Look, C Qiu, M Kandemir US Patent App. 17/231,757, 2021 | | 2021 |
| Method and device for processing sensor data A Look, M Kandemir US Patent App. 17/086,057, 2021 | | 2021 |
| Vorhersage von stationären Strömungsfeldern mit neuronalen Netzen L Harsch, A Look, S Riedelbauch Wasserwirtschaft 109 (9), 56-59, 2019 | | 2019 |
| Prediction of stationary flow fields with neural networks. L Harsch, A Look, S Riedelbauch | | 2019 |
