| Addressing function approximation error in actor-critic methods S Fujimoto, H Hoof, D Meger International Conference on Machine Learning, 1587-1596, 2018 | 8812 | 2018 |
| Attention, Learn to Solve Routing Problems! W Kool, H van Hoof, M Welling arXiv preprint arXiv:1803.08475, 2018 | 2278 | 2018 |
| A research agenda for hybrid intelligence: augmenting human intellect with collaborative, adaptive, responsible, and explainable artificial intelligence Z Akata, D Balliet, M De Rijke, F Dignum, V Dignum, G Eiben, A Fokkens, ... Computer 53 (8), 18-28, 2020 | 586 | 2020 |
| Stochastic beams and where to find them: The gumbel-top-k trick for sampling sequences without replacement W Kool, H Van Hoof, M Welling International Conference on Machine Learning, 3499-3508, 2019 | 325 | 2019 |
| BanditSum: Extractive Summarization as a Contextual Bandit Y Dong, Y Shen, E Crawford, H van Hoof, JCK Cheung arXiv preprint arXiv:1809.09672, 2018 | 248 | 2018 |
| Deep policy dynamic programming for vehicle routing problems W Kool, H van Hoof, J Gromicho, M Welling International Conference on Integration of Constraint Programming …, 2022 | 237 | 2022 |
| Stable reinforcement learning with autoencoders for tactile and visual data H van Hoof, N Chen, M Karl, P van der Smagt, J Peters 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2016 | 229 | 2016 |
| Mdp homomorphic networks: Group symmetries in reinforcement learning E van der Pol, D Worrall, H van Hoof, F Oliehoek, M Welling Advances in Neural Information Processing Systems 33, 2020 | 220 | 2020 |
| Learning Robot In-Hand Manipulation with Tactile Features H van Hoof, T Hermans, G Neumann, J Peters | 210 | 2015 |
| Towards Learning Hierarchical Skills for Multi-Phase Manipulation Tasks O Kroemer, C Daniel, G Neumann, H van Hoof, J Peters Proceedings of the International Conference on Robotics and Automation, 2015 | 173 | 2015 |
| Probabilistic inference for determining options in reinforcement learning C Daniel, H Van Hoof, J Peters, G Neumann Machine Learning 104 (2), 337-357, 2016 | 162 | 2016 |
| A Survey of Exploration Methods in Reinforcement Learning S Amin, M Gomrokchi, H Satija, H van Hoof, D Precup arXiv preprint arXiv:2109.00157, 2021 | 154 | 2021 |
| Buy 4 REINFORCE Samples, Get a Baseline for Free! W Kool, H van Hoof, M Welling | 146 | 2019 |
| Stabilizing novel objects by learning to predict tactile slip F Veiga, H Van Hoof, J Peters, T Hermans 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2015 | 140 | 2015 |
| Active tactile object exploration with gaussian processes Z Yi, R Calandra, F Veiga, H van Hoof, T Hermans, Y Zhang, J Peters 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2016 | 128 | 2016 |
| Keeping dataset biases out of the simulation: A debiased simulator for reinforcement learning based recommender systems J Huang, H Oosterhuis, M De Rijke, H Van Hoof Proceedings of the 14th ACM Conference on Recommender Systems, 190-199, 2020 | 111 | 2020 |
| Deep generative modeling of LiDAR data L Caccia, H Van Hoof, A Courville, J Pineau 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2019 | 88 | 2019 |
| Probabilistic Segmentation and Targeted Exploration of Objects in Cluttered Environments H van Hoof, O Kroemer, J Peters IEEE Transactions on Robotics, 2014 | 87 | 2014 |
| Experimental design for MRI by greedy policy search T Bakker, H van Hoof, M Welling Advances in Neural Information Processing Systems 33, 2020 | 73 | 2020 |
| Estimating Gradients for Discrete Random Variables by Sampling without Replacement W Kool, H van Hoof, M Welling arXiv preprint arXiv:2002.06043, 2020 | 70 | 2020 |
Max WellingCAIO CuspAI & Professor Machine Learning, University of AmsterdamVerified email at uva.nl
