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Robust simulation-based inference in cosmology with Bayesian neural networks.

, , , , , , , и . Mach. Learn. Sci. Technol., 4 (1): 01 (марта 2023)

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Robust simulation-based inference in cosmology with Bayesian neural networks., , , , , , , и . Mach. Learn. Sci. Technol., 4 (1): 01 (марта 2023)Multiple physics pretraining for physical surrogate models, , , , , , , , , и 1 other автор(ы). arXiv preprint arXiv:2310.02994, (2023)Phase Retrieval with Holography and Untrained Priors: Tackling the Challenges of Low-Photon Nanoscale Imaging., , , , и . CoRR, (2020)Multiple Physics Pretraining for Physical Surrogate Models., , , , , , , , , и 4 other автор(ы). CoRR, (2023)Greedy Layerwise Learning Can Scale To ImageNet., , и . ICML, том 97 из Proceedings of Machine Learning Research, стр. 583-593. PMLR, (2019)Greedy Layerwise Learning Can Scale to ImageNet, , и . (2018)cite arxiv:1812.11446.Local Learning with Neuron Groups., , и . CoRR, (2023)Robust Simulation-Based Inference in Cosmology with Bayesian Neural Networks., , , , , , , и . CoRR, (2022)Can Forward Gradient Match Backpropagation?, , , , и . ICML, том 202 из Proceedings of Machine Learning Research, стр. 10249-10264. PMLR, (2023)Phase Retrieval with Holography and Untrained Priors: Tackling the Challenges of Low-Photon Nanoscale Imaging., , , , и . MSML, том 145 из Proceedings of Machine Learning Research, стр. 516-567. PMLR, (2021)