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Editors: James Urquhart Allingham, Siddharth Swaroop
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Deep Q-Exponential Processes
; Proceedings of the 7th Symposium on Advances in Approximate Bayesian Inference, PMLR 289:1-24
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Massively Parallel Expectation Maximization For Approximate Posteriors
Thomas Heap, Sam Bowyer, Laurence Aitchison; Proceedings of the 7th Symposium on Advances in Approximate Bayesian Inference, PMLR 289:25-66
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From predictions to confidence intervals: an empirical study of conformal prediction methods for in-context learning
Zhe Huang, Simone Rossi, Rui Yuan, Thomas Hannagan; Proceedings of the 7th Symposium on Advances in Approximate Bayesian Inference, PMLR 289:67-90
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Normalizing Flow Regression for Bayesian Inference with Offline Likelihood Evaluations
Chengkun Li, Bobby Huggins, Petrus Mikkola, Luigi Acerbi; Proceedings of the 7th Symposium on Advances in Approximate Bayesian Inference, PMLR 289:91-130
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$U$-ensembles: Improved diversity in the small data regime using unlabeled data
Konstantinos Pitas, Hani Anouar Bourrous, Julyan Arbel; Proceedings of the 7th Symposium on Advances in Approximate Bayesian Inference, PMLR 289:131-167
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Divide, Conquer, Combine Bayesian Decision Tree Sampling
Jodie A. Cochrane, Adrian Wills, Sarah J. Johnson; Proceedings of the 7th Symposium on Advances in Approximate Bayesian Inference, PMLR 289:168-193
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Sparse Gaussian Neural Processes
Tommy Rochussen, Vincent Fortuin; Proceedings of the 7th Symposium on Advances in Approximate Bayesian Inference, PMLR 289:194-219
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