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- Centre National de la Recherche ScientifiqueFR14 papers
- Institut national de recherche en sciences et technologies du numériqueFR14 papers
- National Institute of InformaticsJP13 papers
- SupélecFR13 papers
- University of Illinois ChicagoUS10 papers
- Technical University of MunichDE9 papers
- Laboratoire Informatique d'AvignonFR8 papers
- University College LondonGB8 papers
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- Sorbonne UniversitéFR7 papers
- Université Côte d'AzurFR7 papers
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Showing 2019 · stat.MLShow all
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stat.ML2019
Efficient Approximate Inference with Walsh-Hadamard Variational Inference
Simone Rossi, Sebastien Marmin, Maurizio Filippone
Variational inference offers scalable and flexible tools to tackle intractable Bayesian inference of modern statistical models like Bayesian neural networks and Gaussian processes.…
stat.ML2019★ 4 cited
Walsh-Hadamard Variational Inference for Bayesian Deep Learning
Simone Rossi, Sebastien Marmin, Maurizio Filippone
Over-parameterized models, such as DeepNets and ConvNets, form a class of models that are routinely adopted in a wide variety of applications, and for which Bayesian inference is d…