Publications

Son Luu, Zuheng Xu, Nikola Surjanovic, Miguel Biron-Lattes, Trevor Campbell, Alexandre Bouchard-Côté (2024). Is Gibbs sampling faster than Hamiltonian Monte Carlo on GLMs?. Submitted.

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Tiange Liu, Nikola Surjanovic, Miguel Biron-Lattes, Alexandre Bouchard-Côté, Trevor Campbell (2024). AutoStep --- Locally adaptive involutive MCMC. Submitted.

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Nikola Surjanovic, Saifuddin Syed, Alexandre Bouchard-Côté, Trevor Campbell (2024). Uniform ergodicity of parallel tempering with efficient local exploration. Submitted.

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Miguel Biron-Lattes, Nikola Surjanovic, Saifuddin Syed, Trevor Campbell, Alexandre Bouchard-Côté (2024). autoMALA --- Locally adaptive Metropolis-adjusted Langevin algorithm. International Conference on Artificial Intelligence and Statistics.

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Alexandre Bouchard-Côté, Trevor Campbell, Geoff Pleiss, Nikola Surjanovic (2024). MCMC-driven learning. To appear in the Handbook of Markov Chain Monte Carlo.

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Nikola Surjanovic, Andrew Henrey, Thomas M. Loughin (2024). Alpha-trimming --- Locally adaptive tree pruning for random forests.

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Nikola Surjanovic, Miguel Biron-Lattes, Paul Tiede, Saifuddin Syed, Trevor Campbell, Alexandre Bouchard-Côté (2023). Pigeons.jl --- Distributed Sampling From Intractable Distributions. Submitted.

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Nikola Surjanovic, Thomas M. Loughin (2023). Improving the Hosmer-Lemeshow goodness-of-fit test in large models with replicated Bernoulli trials. Journal of Applied Statistics.

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Nikola Surjanovic, Richard Lockhart, Thomas M. Loughin (2023). A generalized Hosmer-Lemeshow goodness-of-fit test for a family of generalized linear models. TEST.

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Nikola Surjanovic, Saifuddin Syed, Alexandre Bouchard-Côté, Trevor Campbell (2022). Parallel tempering with a variational reference. Advances in Neural Information Processing Systems.

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Meghan McPherson, Kristin Houghton, Nikola Surjanovic, Thomas M. Loughin (2022). Development and Validation of the Kids Disability Screen for Children with Juvenile Idiopathic Arthritis --- Results from the CAPRI Registry. Published in Rheumatology (Oxford).

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Nikola Surjanovic (2021). An efficient approach to pruning regression trees using a modified Bayesian information criterion. Master’s thesis.

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