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

, , , , , , , and . Mach. Learn. Sci. Technol., 4 (1): 01 (March 2023)

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