| Equivariant representation learning via class-pose decomposition GL Marchetti, G Tegnér, A Varava, D Kragic International Conference on Artificial Intelligence and Statistics, 4745-4756, 2023 | 16 | 2023 |
| Recurrent neural networks for financial asset forecasting G Tegnér | 7 | 2018 |
| Self-Supervised Latent Symmetry Discovery via Class-Pose Decomposition G Tegnér, H Kjellstrom NeurIPS 2023 Workshop on Symmetry and Geometry in Neural Representations, 2023 | 1 | 2023 |
| On the Subspace Structure of Gradient-Based Meta-Learning G Tegnér, A Reichlin, H Yin, M Björkman, D Kragic arXiv preprint arXiv:2207.03804, 2022 | 1 | 2022 |
| Reducing Variance in Meta-Learning via Laplace Approximation for Regression Tasks A Reichlin, G Tegnér, M Vasco, H Yin, M Björkman, D Kragic arXiv preprint arXiv:2410.01476, 2024 | | 2024 |
| Learning Coarsened Dynamic Graph Representations for Deformable Object Manipulation GL Marchetti, M Moletta, G Tegnér, P Shi, A Varava, A Kravchenko, ... 2021 20th International Conference on Advanced Robotics (ICAR), 955-960, 2021 | | 2021 |
| Variance-Reduced Meta-Learning via Laplace Approximation G Tegnér, A Reichlin, H Yin, M Björkman, D Kragic | | |
| Gradient-Based Transfer Learning G Tegnér, A Reichlin, H Yin, H Kjellstrom, M Björkman, D Kragic | | |
