Deep Q-Exponential Processes

Zhi Chang, Chukwudi Paul Obite, Shuang Zhou, Shiwei Lan; 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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