Differentiation of blackbox combinatorial solvers MV Pogančić, A Paulus, V Musil, G Martius, M Rolinek International Conference on Learning Representations, 2020 | 322* | 2020 |
Deep graph matching via blackbox differentiation of combinatorial solvers M Rolínek, P Swoboda, D Zietlow, A Paulus, V Musil, G Martius Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020 | 114 | 2020 |
Optimizing rank-based metrics with blackbox differentiation M Rolínek, V Musil, A Paulus, M Vlastelica, C Michaelis, G Martius Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 107 | 2020 |
Comboptnet: Fit the right np-hard problem by learning integer programming constraints A Paulus, M Rolínek, V Musil, B Amos, G Martius International Conference on Machine Learning, 8443-8453, 2021 | 72 | 2021 |
Advprompter: Fast adaptive adversarial prompting for llms A Paulus, A Zharmagambetov, C Guo, B Amos, Y Tian arXiv preprint arXiv:2404.16873, 2024 | 27 | 2024 |
Backpropagation through combinatorial algorithms: Identity with projection works SS Sahoo, A Paulus, M Vlastelica, V Musil, V Kuleshov, G Martius arXiv preprint arXiv:2205.15213, 2022 | 21 | 2022 |
LPGD: A General Framework for Backpropagation through Embedded Optimization Layers A Paulus, G Martius, V Musil arXiv preprint arXiv:2407.05920, 2024 | | 2024 |
Lagrangian Proximal Gradient Descent for Learning Convex Optimization Models A Paulus, G Martius, V Musil | | |
4.13 Blackbox Differentiation: Empower Deep Networks with Combinatorial Algorithms G Martius, A Paulus Machine Learning and Logical Reasoning: The New Frontier, 100, 0 | | |