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56 Results
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Poster
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Wed 9:00 |
Understanding Non-linearity in Graph Neural Networks from the Bayesian-Inference Perspective Rongzhe Wei · Haoteng YIN · Junteng Jia · Austin Benson · Pan Li |
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Poster
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Thu 14:00 |
Black-box coreset variational inference Dionysis Manousakas · Hippolyt Ritter · Theofanis Karaletsos |
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Poster
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Tue 14:00 |
Fast Bayesian Inference with Batch Bayesian Quadrature via Kernel Recombination Masaki Adachi · Satoshi Hayakawa · Martin Jørgensen · Harald Oberhauser · Michael A Osborne |
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Poster
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Wed 9:00 |
Bayesian Clustering of Neural Spiking Activity Using a Mixture of Dynamic Poisson Factor Analyzers Ganchao Wei · Ian H Stevenson · Xiaojing Wang |
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Workshop
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Generative Posterior Networks for Approximately Bayesian Epistemic Uncertainty Estimation Melrose Roderick · Felix Berkenkamp · Fatemeh Sheikholeslami · J. Zico Kolter |
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Poster
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Wed 9:00 |
Invariance Learning in Deep Neural Networks with Differentiable Laplace Approximations Alexander Immer · Tycho van der Ouderaa · Gunnar Rätsch · Vincent Fortuin · Mark van der Wilk |
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Poster
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Wed 9:00 |
Batch Bayesian optimisation via density-ratio estimation with guarantees Rafael Oliveira · Louis Tiao · Fabio Ramos |
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Workshop
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Approximate Bayesian Computation for Panel Data with Signature Maximum Mean Discrepancies Joel Dyer · John Fitzgerald · Bastian Rieck · Sebastian Schmon |
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Poster
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Accelerated Linearized Laplace Approximation for Bayesian Deep Learning Zhijie Deng · Feng Zhou · Jun Zhu |
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Poster
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Tue 9:00 |
Laplacian Autoencoders for Learning Stochastic Representations Marco Miani · Frederik Warburg · Pablo Moreno-Muñoz · Nicki Skafte · Søren Hauberg |
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Poster
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Thu 14:00 |
Bayesian Risk Markov Decision Processes Yifan Lin · Yuxuan Ren · Enlu Zhou |
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Poster
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Para-CFlows: Ck-universal diffeomorphism approximators as superior neural surrogates Junlong Lyu · Zhitang Chen · Chang Feng · Wenjing Cun · Shengyu Zhu · Yanhui Geng · ZHIJIE XU · Chen Yongwei |