Likelihood-free MCMC with Amortized Approximate Ratio Estimators J Hermans, V Begy, G Louppe arXiv preprint arXiv:1903.04057, 2019 | 189* | 2019 |
Mining for Dark Matter Substructure: Inferring subhalo population properties from strong lenses with machine learning J Brehmer, S Mishra-Sharma, J Hermans, G Louppe, K Cranmer The Astrophysical Journal 886 (1), 49, 2019 | 106 | 2019 |
A crisis in simulation-based inference? beware, your posterior approximations can be unfaithful J Hermans, A Delaunoy, F Rozet, A Wehenkel, G Louppe Transactions on Machine Learning Research, 2022 | 86* | 2022 |
Adversarial variational optimization of non-differentiable simulators G Louppe, J Hermans, K Cranmer The 22nd International Conference on Artificial Intelligence and Statistics …, 2019 | 70 | 2019 |
Towards constraining warm dark matter with stellar streams through neural simulation-based inference J Hermans, N Banik, C Weniger, G Bertone, G Louppe Monthly Notices of the Royal Astronomical Society 507 (2), 1999-2011, 2021 | 40 | 2021 |
Accumulated gradient normalization JR Hermans, G Spanakis, R Möckel Asian Conference on Machine Learning, 439-454, 2017 | 30 | 2017 |
Towards reliable simulation-based inference with balanced neural ratio estimation A Delaunoy, J Hermans, F Rozet, A Wehenkel, G Louppe Advances in Neural Information Processing Systems 35, 20025-20037, 2022 | 24 | 2022 |
Distributed keras: Distributed deep learning with apache spark and keras JR Hermans CERN IT-DB, 2016 | 15* | 2016 |
On Scalable Deep Learning and Parallelizing Gradient Descent JR Hermans https://cds.cern.ch/record/2276711, 2017 | 14 | 2017 |
A trust crisis in simulation-based inference J Hermans, A Delaunoy, F Rozet, A Wehenkel, V Begy, G Louppe Your posterior approximations can be unfaithful, 2021 | 7 | 2021 |
Hypothesis J Hermans, V Begy GitHub repository, 2019 | 6 | 2019 |
Developing and optimizing applications in hadoop P Kothuri, D Garcia, J Hermans Journal of Physics: Conference Series 898 (7), 072038, 2017 | 3 | 2017 |
Advances in Simulation-Based Inference: Towards the automation of the Scientific Method through Learning Algorithms J Hermans ULiège-University of Liège [Faculty of Applied Sciences], Belgium, 2022 | 2 | 2022 |
Gradient energy matching for distributed asynchronous gradient descent J Hermans, G Louppe arXiv preprint arXiv:1805.08469, 2018 | 2 | 2018 |
Simulating Data Access Profiles of Computational Jobs in Data Grids V Begy, J Hermans, M Barisits, M Lassnig, E Schikuta 2019 15th International Conference on eScience (eScience), 394-402, 2019 | 1 | 2019 |
Probing Dark Matter Substructure with Stellar Streams and Neural Simulation-Based Inference J Hermans, N Banik, C Weniger, G Bertone, G Louppe Machine Learning and the Physical Sciences. Workshop at the 34th Conference …, 2020 | | 2020 |