| Erdos goes neural: an unsupervised learning framework for combinatorial optimization on graphs N Karalias, A Loukas NeurIPS 2020 34th Conference on Neural Information Processing Systems, Vancouver, 2020 | 86 | 2020 |
| Partition and code: learning how to compress graphs G Bouritsas, A Loukas, N Karalias, M Bronstein Advances in Neural Information Processing Systems 34, 18603-18619, 2021 | 17 | 2021 |
| Neural Set Function Extensions: Learning with Discrete Functions in High Dimensions N Karalias, J Robinson, A Loukas, S Jegelka Advances in Neural Information Processing Systems 35 (NeurIPS 2022), 15338 …, 2022 | 4 | 2022 |
| Probabilistic methods for neural combinatorial optimization N Karalias EPFL, 2023 | 1 | 2023 |
| Are Graph Neural Networks Optimal Approximation Algorithms? M Yau, E Lu, N Karalias, J Xu, S Jegelka arXiv preprint arXiv:2310.00526, 2023 | | 2023 |
| Neural Extensions: Training Neural Networks with Set Functions N Karalias, JD Robinson, A Loukas, S Jegelka | | 2021 |
| LTS2 N Aspert, L Bagnato, E Bayram, R Boulandet, M Boulougouri, X Bresson, ... | | |
Andreas LoukasSenior Principal Scientist, Prescient Design, gRED, RocheBestätigte E-Mail-Adresse bei roche.com
