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Understanding Pathologies of Deep Heteroskedastic Regression
Eliot Wong-Toi, Alex Boyd, Vincent Fortuin, Stephan Mandt
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Laplace-Approximated Neural Additive Models: Improving Interpretability with Bayesian Inference
Kouroche Bouchiat, Alexander Immer, Hugo Yèche, Gunnar Rätsch, Vincent Fortuin
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Incorporating Unlabelled Data into Bayesian Neural Networks
Mrinank Sharma, Tom Rainforth, Yee Whye Teh, Vincent Fortuin
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Promises and Pitfalls of the Linearized Laplace in Bayesian Optimization
Agustinus Kristiadi, Alexander Immer, Runa Eschenhagen, Vincent Fortuin
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PAC-Bayesian Meta-Learning: From Theory to Practice
Jonas Rothfuss, Martin Josifoski, Vincent Fortuin, Andreas Krause
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Sparse Gaussian Process Variational Autoencoders
Matthew Ashman, Jonathan So, Will Tebbutt, Vincent Fortuin, Michael Pearce, Richard E Turner
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Supervised learning on synthetic data for reverse engineering gene regulatory networks from experimental time-series
Stefan Ganscha, Vincent Fortuin, Max Horn, Eirini Arvaniti, Manfred Claassen
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