| Robust scheduling with GFlowNets DW Zhang, C Rainone, M Peschl, R Bondesan International Conference on Learning Representations (ICLR) 2023, 2023 | 37 | 2023 |
| MORAL: Aligning AI with Human Norms through Multi-Objective Reinforced Active Learning M Peschl, A Zgonnikov, FA Oliehoek, LC Siebert AAMAS '22: Proceedings of the 21st International Conference on Autonomous …, 2022 | 29 | 2022 |
| Training for implicit norms in deep reinforcement learning agents through adversarial multi-objective reward optimization M Peschl Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society, 275-276, 2021 | 6 | 2021 |
| Learning perturbations for soft-output linear mimo demappers DE Worrall, M Peschl, A Behboodi, R Bondesan GLOBECOM 2022-2022 IEEE Global Communications Conference, 5213-5218, 2022 | 1 | 2022 |
| NeuroSteiner: A Graph Transformer for Wirelength Estimation S Manchanda, D Kianfar, M Peschl, R Lepert, M Defferrard arXiv preprint arXiv:2407.03792, 2024 | | 2024 |
| Probabilistic and Differentiable Wireless Simulation with Geometric Transformers T Hehn, M Peschl, T Orekondy, A Behboodi, J Brehmer arXiv preprint arXiv:2406.14995, 2024 | | 2024 |
| Robust scheduling with generative flow networks C Rainone, WD Zhang, R Bondesan, M Peschl, M Gagrani, W Jeon, ... US Patent App. 18/459,277, 2024 | | 2024 |
| Geometric Wireless Simulation with Equivariant Transformers T Hehn, M Peschl, T Orekondy, A Behboodi, J Brehmer ICML 2024 Workshop on Geometry-grounded Representation Learning and …, 2024 | | 2024 |
| Lattice reduction-aided perturbed additive demapper for multiple-input multiple-output signal detection M Peschl, DE Worrall, A Behboodi, R Bondesan, P Sadeghi, S Barghi US Patent App. 18/155,454, 2023 | | 2023 |
| Aligning AI with Human Norms: Multi-Objective Deep Reinforcement Learning with Active Preference Elicitation M Peschl | | 2021 |
| Differentiable Wireless Simulation with Geometric Transformers T Hehn, M Peschl, T Orekondy, A Behboodi, J Brehmer ICML 2024 Workshop on Differentiable Almost Everything: Differentiable …, 0 | | |
Roberto BondesanImperial College LondonVerified email at imperial.ac.uk
