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Results: 36
Number of items: 36
  • Open Access
    Abbott, R., LIGO Scientific Collaboration, Virgo Collaboration, & KAGRA Collaboration (2022). Search for continuous gravitational wave emission from the Milky Way center in O3 LIGO-Virgo data. Physical Review D. Particles, Fields, Gravitation, and Cosmology, 106(4), Article 042003. https://doi.org/10.1103/PhysRevD.106.042003
  • Open Access
    Abbott, R., LIGO Scientific Collaboration, The Virgo Collaboration, & The KAGRA Collaboration (2022). All-sky, all-frequency directional search for persistent gravitational waves from Advanced LIGO's and Advanced Virgo's first three observing runs. Physical Review D. Particles, Fields, Gravitation, and Cosmology, 105(12), Article 122001. https://doi.org/10.1103/PhysRevD.105.122001
  • Open Access
    Abbott, R., The LIGO Scientific Collaboration, The Virgo Collaboration, & KAGRA Collaboration (2022). All-sky search for gravitational wave emission from scalar boson clouds around spinning black holes in LIGO O3 data. Physical Review D. Particles, Fields, Gravitation, and Cosmology, 105(10), Article 102001. https://doi.org/10.1103/PhysRevD.105.102001
  • Open Access
    Cole, A., Forre, P., Louppe, G., Miller, B. K., & Weniger, C. (2022). Truncated Marginal Neural Ratio Estimation. In M. Ranzato, A. Beygelzimer, Y. Dauphin, P. S. Liang, & J. Wortman Vaughan (Eds.), 35th Conference on Neural Information Processing Systems (NeurIPS 2021) : online, 6-14 December 2021 (Vol. 1, pp. 129-143). (Advances in Neural Information Processing Systems; Vol. 34). Neural Information Processing Systems Foundation. https://papers.nips.cc/paper/2021/hash/01632f7b7a127233fa1188bd6c2e42e1-Abstract.html
  • Miller, B. K., Cole, A., Forré, P., Louppe, G., & Weniger, C. (2021). Truncated Marginal Neural Ratio Estimation - Data [Data set]. Zenodo. https://doi.org/10.5281/zenodo.5592427
  • Open Access
    Miller, B. K., Cole, A., Louppe, G., & Weniger, C. (2020). Simulation-efficient marginal posterior estimation with swyft: Stop wasting your precious time. Paper presented at Third Workshop on Machine Learning and the Physical Sciences (NeurIPS 2020), Vancouver, Canada. https://ml4physicalsciences.github.io/2020/files/NeurIPS_ML4PS_2020_106.pdf
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