| Relevance of rotationally equivariant convolutions for predicting molecular properties BK Miller, M Geiger, TE Smidt, F Noé arXiv preprint arXiv:2008.08461, 2020 | 84 | 2020 |
| Euclidean neural networks: e3nn, April 2022 M Geiger, T Smidt, M Alby, BK Miller, W Boomsma, B Dice, K Lapchevskyi, ... URL https://doi. org/10.5281/zenodo 6459381 (4), 0 | 71* | |
| Finding symmetry breaking order parameters with euclidean neural networks TE Smidt, M Geiger, BK Miller Physical Review Research 3 (1), L012002, 2021 | 62 | 2021 |
| Fast and credible likelihood-free cosmology with truncated marginal neural ratio estimation A Cole, BK Miller, SJ Witte, MX Cai, MW Grootes, F Nattino, C Weniger Journal of Cosmology and Astroparticle Physics 2022 (09), 004, 2022 | 58 | 2022 |
| Truncated marginal neural ratio estimation BK Miller, A Cole, P Forré, G Louppe, C Weniger Advances in Neural Information Processing Systems 34, 129-143, 2021 | 48 | 2021 |
| Generative coarse-graining of molecular conformations W Wang, M Xu, C Cai, BK Miller, T Smidt, Y Wang, J Tang, ... arXiv preprint arXiv:2201.12176, 2022 | 43 | 2022 |
| Sequential simulation-based inference for gravitational wave signals U Bhardwaj, J Alvey, BK Miller, S Nissanke, C Weniger Physical Review D 108 (4), 042004, 2023 | 41 | 2023 |
| Contrastive neural ratio estimation BK Miller, C Weniger, P Forré Advances in Neural Information Processing Systems 35, 3262-3278, 2022 | 28 | 2022 |
| swyft: Truncated Marginal Neural Ratio Estimation in Python BK Miller, A Cole, C Weniger, F Nattino, O Ku, MW Grootes Journal of Open Source Software 7 (75), 4205, 2022 | 23 | 2022 |
| Simulation-efficient marginal posterior estimation with swyft: stop wasting your precious time BK Miller, A Cole, G Louppe, C Weniger arXiv preprint arXiv:2011.13951, 2020 | 19 | 2020 |
| Flowmm: Generating materials with riemannian flow matching BK Miller, RTQ Chen, A Sriram, BM Wood Forty-first International Conference on Machine Learning, 2024 | 17 | 2024 |
| Balancing simulation-based inference for conservative posteriors A Delaunoy, BK Miller, P Forré, C Weniger, G Louppe arXiv preprint arXiv:2304.10978, 2023 | 9 | 2023 |
| Flowllm: Flow matching for material generation with large language models as base distributions A Sriram, B Miller, RTQ Chen, B Wood Advances in Neural Information Processing Systems 37, 46025-46046, 2024 | 8 | 2024 |
| Simulation-based Inference with the Generalized Kullback-Leibler Divergence BK Miller, M Federici, C Weniger, P Forré Synergy of Scientific and Machine Learning Modeling Workshop at the …, 2023 | 4 | 2023 |
| Automatically detecting anomalous exoplanet transits CJ Hönes, BK Miller, AM Heras, BH Foing arXiv preprint arXiv:2111.08679, 2021 | 2 | 2021 |
| Classical analysis of high harmonic generation K Miller Thesis, University of Colorado, Boulder, 2015 | 2 | 2015 |
| SE (3) Equivariant Neural Networks for Regression on Molecular Properties: The QM9 Benchmark BK Miller | 1 | 2020 |
| All-atom Diffusion Transformers: Unified generative modelling of molecules and materials CK Joshi, X Fu, YL Liao, V Gharakhanyan, BK Miller, A Sriram, ZW Ulissi arXiv preprint arXiv:2503.03965, 2025 | | 2025 |
| sbi reloaded: a toolkit for simulation-based inference workflows J Boelts, M Deistler, M Gloeckler, Á Tejero-Cantero, JM Lueckmann, ... arXiv preprint arXiv:2411.17337, 2024 | | 2024 |
| Machine learning for scientific simulation: Inference and generative models BK Miller | | 2024 |
Christoph WenigerAssociate Professor of Physics, University of AmsterdamEmail confirmado em uva.nl