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A Scalable Laplace Approximation for Neural Networks

, , and . International Conference on Learning Representations, (2018)

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Hamiltonian Generative Networks, , , , , and . International Conference on Learning Representations, (2020)Hamiltonian Generative Networks., , , , , and . CoRR, (2019)A Scalable Laplace Approximation for Neural Networks, , and . International Conference on Learning Representations, (2018)Normalizing flows for lattice gauge theory in arbitrary space-time dimension., , , , , , , , , and 4 other author(s). CoRR, (2023)Disentangling by Subspace Diffusion., , , and . NeurIPS, (2020)Aspects of scaling and scalability for flow-based sampling of lattice QCD., , , , , , , , , and 3 other author(s). CoRR, (2022)Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models., , , , , , , , , and 7 other author(s). CoRR, (2024)The Gauss-Newton matrix for Deep Learning models and its applications.. University College London, UK, (2020)British Library, EThOS.Hamiltonian Generative Networks., , , , , and . ICLR, OpenReview.net, (2020)Deep Transformers without Shortcuts: Modifying Self-attention for Faithful Signal Propagation., , , , , , and . ICLR, OpenReview.net, (2023)