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Video Representation Learning for Decoupled Deep Reinforcement Learning Applied to Autonomous Driving2023 IEEE/SICE International Symposium on System Integration (SII) conference-paper Computer Science Reinforcement Learning in Robotics
Shawan Taha Mohammed, Mohamed Kastouri, Artur Niederfahrenhorst, Gerd Ascheid
1citations -
NMDA-driven dendritic modulation enables multitask representation learning in hierarchical sensory processing pathways2023 Proceedings of the National Academy of Sciences article Neuroscience Neural dynamics and brain function Open access
Willem A. M. Wybo, Matthias C. Tsai, Viet Anh Tran, Bernd Illing, Jakob Jordan, Abigail Morrison, +1 more
25citations -
Representation Learning for Tablet and Paper Domain Adaptation in Favor of Online Handwriting Recognition2023 Lecture notes in computer science conference-paper Computer Science Domain Adaptation and Few-Shot Learning Open access
Felix Ott, David Rügamer, Lucas Heublein, Bernd Bischl, Christopher Mutschler
4citations -
Physics-based machine learning for modeling thermo-hydraulic processes in a coaxial deep borehole heat exchanger, considering an explicit reservoir-wellbore representation: A case study of Cornwall, UK
Dimitra Teza, Ryan Santoso, Nora Koltzer, Denise Degen, Tony Bennett, Florian Wellmann
0citations -
Accurate Distances Measures and Machine Learning of the Texture-Property Relation for Crystallographic Textures Represented by One-Point Statistics2023 arXiv (Cornell University) preprint Materials Science Machine Learning in Materials Science Open access
Tarek Iraki, Lukas Morand, Norbert Link, Stefan Sandfeld, Dirk Helm
0citations -
Tree-Based Learning on Amperometric Time Series Data Demonstrates High Accuracy for Classification2023 arXiv (Cornell University) preprint Chemistry Electrochemical Analysis and Applications Open access
Jeyashree Krishnan, Zeyu Lian, Pieter E. Oomen, Xiulan He, Soodabeh Majdi, Andreas Schuppert, +1 more
1citations -
Towards Foundational Models for Molecular Learning on Large-Scale Multi-Task Datasets (Ultra Large Dataset)2023 Zenodo (CERN European Organization for Nuclear Research) preprint Computer Science Computational Drug Discovery Methods Open access
Dominique Beaini, Shenyang Huang, Joao Alex Cunha, Zhiyi Li, Gabriela Moisescu-Pareja, Oleksandr Dymov, +20 more
0citations -
Towards Foundational Models for Molecular Learning on Large-Scale Multi-Task Datasets2023 Zenodo (CERN European Organization for Nuclear Research) preprint Computer Science Computational Drug Discovery Methods Open access
Dominique Beaini, Shenyang Huang, Joao Alex Cunha, Zhiyi Li, Gabriela Moisescu-Pareja, Oleksandr Dymov, +20 more
0citations -
Towards Foundational Models for Molecular Learning on Large-Scale Multi-Task Datasets2023 Zenodo (CERN European Organization for Nuclear Research) preprint Computer Science Computational Drug Discovery Methods Open access
Dominique Beaini, Shenyang Huang, Joao Alex Cunha, Zhiyi Li, Gabriela Moisescu-Pareja, Oleksandr Dymov, +20 more
0citations -
Towards Foundational Models for Molecular Learning on Large-Scale Multi-Task Datasets (Ultra Large Dataset)2023 Zenodo (CERN European Organization for Nuclear Research) preprint Computer Science Computational Drug Discovery Methods Open access
Dominique Beaini, Shenyang Huang, Joao Alex Cunha, Zhiyi Li, Gabriela Moisescu-Pareja, Oleksandr Dymov, +20 more
0citations -
Towards Foundational Models for Molecular Learning on Large-Scale Multi-Task Datasets2023 Zenodo (CERN European Organization for Nuclear Research) preprint Computer Science Computational Drug Discovery Methods Open access
Dominique Beaini, Shenyang Huang, Joao Alex Cunha, Zhiyi Li, Gabriela Moisescu-Pareja, Oleksandr Dymov, +19 more
0citations -
Towards Foundational Models for Molecular Learning on Large-Scale Multi-Task Datasets2023 Zenodo (CERN European Organization for Nuclear Research) preprint Computer Science Computational Drug Discovery Methods Open access
Dominique Beaini, Shenyang Huang, Joao Alex Cunha, Zhiyi Li, Gabriela Moisescu-Pareja, Oleksandr Dymov, +20 more
0citations