| Multimodal representation learning for place recognition using deep Hebbian predictive coding MJ Pearson, S Dora, O Struckmeier, TC Knowles, B Mitchinson, K Tiwari, ... Frontiers in Robotics and AI 8, 732023, 2021 | 21 | 2021 |
| ViTa-SLAM: A Bio-inspired Visuo-Tactile SLAM for Navigation while Interacting with Aliased Environments O Struckmeier, K Tiwari, M Salman, MJ Pearson, V Kyrki arXiv preprint arXiv:1906.06422, 2019 | 19 | 2019 |
| Autonomous Generation of Robust and Focused Explanations for Robot Policies O Struckmeier, M Racca, V Kyrki 2019 28th IEEE International Conference on Robot and Human Interactive …, 2019 | 10 | 2019 |
| MuPNet: Multi-modal Predictive Coding Network for Place Recognition by Unsupervised Learning of Joint Visuo-Tactile Latent Representations O Struckmeier, K Tiwari, S Dora, MJ Pearson, SM Bohte, C Pennartz, ... arXiv preprint arXiv:1909.07201, 2019 | 3 | 2019 |
| LeagueAI: Improving object detector performance and flexibility through automatically generated training data and domain randomization O Struckmeier arXiv preprint arXiv:1905.13546, 2019 | 3 | 2019 |
| Autoencoding slow representations for semi-supervised data-efficient regression O Struckmeier, K Tiwari, V Kyrki Machine Learning 112 (7), 2297-2315, 2023 | 2 | 2023 |
| Learning representations that are closed-form Monge mapping optimal with application to domain adaptation O Struckmeier, I Redko, A Mallasto, K Arndt, M Heinonen, V Kyrki Transactions on Machine Learning Research, 2023 | 1 | 2023 |
| Domain Curiosity: Learning Efficient Data Collection Strategies for Domain Adaptation K Arndt, O Struckmeier, V Kyrki 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2021 | 1 | 2021 |
| Unsupervised Learning of slow features for Data Efficient Regression O Struckmeier, K Tiwari, V Kyrki arXiv preprint arXiv:2012.06279, 2020 | 1 | 2020 |
| Representation learning methods for robotic perception and learning—at the intersection of computational neuroscience and machine learning O Struckmeier Aalto University, 2024 | | 2024 |
| Understanding deep neural networks through the lens of their non-linearity Q Bouniot, I Redko, A Mallasto, C Laclau, K Arndt, O Struckmeier, ... arXiv preprint arXiv:2310.11439, 2023 | | 2023 |
| ILPO-MP: Mode Priors Prevent Mode Collapse when Imitating Latent Policies from Observations O Struckmeier, V Kyrki Transactions on Machine Learning Research, 2023 | | 2023 |
| Beyond invariant representation learning: linearly alignable latent spaces for efficient closed-form domain adaptation O Struckmeier, I Redko, A Mallasto, K Arndt, M Heinonen, V Kyrki arXiv preprint arXiv:2305.07500, 2023 | | 2023 |
| Preventing Mode Collapse When Imitating Latent Policies from Observations O Struckmeier, V Kyrki | | 2022 |
| Unsupervised Learning of Slow Features for Data Efficient Regression O Struckmeier, K Tiwari, V Kyrki | | 2020 |
| ViTa-SLAM O Struckmeier, K Tiwari, M Salman, MJ Pearson, V Kyrki IEEE International Conference on Cyborg and Bionic Systems, 2019 | | 2019 |
| Generating Explanations of Robot Policies in Continuous State Spaces O Struckmeier Aalto University, 2018 | | 2018 |
| Teach-In für die 3D-Scan Akquise mit einem Roboter O STRUCKMEIER, D BORRMANN, A NÜCHTER https://www.jade-hs.de/unsere-hochschule/fachbereiche/bgg/geoinformation …, 2017 | | 2017 |
Ville KyrkiProfessor at Aalto UniversityZweryfikowany adres z aalto.fi
