Trevor Campbell
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
19
Venues
4
Active years
2014–2025
Best venue rank
A*
Where they publish
Papers
19 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | AISTATS | Is Gibbs sampling faster than Hamiltonian Monte Carlo on GLMs? | Son Luu, Zuheng Xu, Nikola Surjanovic, Miguel Biron-Lattes, Trevor Campbell, Alexandre Bouchard-Ct |
| 2025 | ICML | Tuning Sequential Monte Carlo Samplers via Greedy Incremental Divergence Minimization. | Kyurae Kim, Zuheng Xu, Jacob R. Gardner, Trevor Campbell |
| 2025 | ICML | AutoStep: Locally adaptive involutive MCMC. | Tiange Liu, Nikola Surjanovic, Miguel Biron-Lattes, Alexandre Bouchard-Ct, Trevor Campbell |
| 2025 | UAI | Tuning-Free Coreset Markov Chain Monte Carlo via Hot DoG. | Naitong Chen, Jonathan H. Huggins, Trevor Campbell |
| 2024 | AISTATS | autoMALA: Locally adaptive Metropolis-adjusted Langevin algorithm. | Miguel Biron-Lattes, Nikola Surjanovic, Saifuddin Syed, Trevor Campbell, Alexandre Bouchard-Ct |
| 2024 | AISTATS | Coreset Markov chain Monte Carlo. | Naitong Chen, Trevor Campbell |
| 2024 | AISTATS | Mixed variational flows for discrete variables. | Gian Carlo Diluvi, Benjamin Bloem-Reddy, Trevor Campbell |
| 2023 | ICML | MixFlows: principled variational inference via mixed flows. | Zuheng Xu, Naitong Chen, Trevor Campbell |
| 2021 | ICML | Finite mixture models do not reliably learn the number of components. | Diana Cai, Trevor Campbell, Tamara Broderick |
| 2021 | ICML | Parallel tempering on optimized paths. | Saifuddin Syed, Vittorio Romaniello, Trevor Campbell, Alexandre Bouchard-Ct |
| 2021 | UAI | Sequential core-set Monte Carlo. | Boyan Beronov, Christian Weilbach, Frank Wood, Trevor Campbell |
| 2020 | AISTATS | Validated Variational Inference via Practical Posterior Error Bounds. | Jonathan H. Huggins, Mikolaj J. Kasprzak, Trevor Campbell, Tamara Broderick |
| 2020 | UAI | Slice Sampling for General Completely Random Measures. | Peiyuan Zhu, Alexandre Bouchard-Ct, Trevor Campbell |
| 2019 | AISTATS | Data-dependent compression of random features for large-scale kernel approximation. | Raj Agrawal, Trevor Campbell, Jonathan H. Huggins, Tamara Broderick |
| 2019 | AISTATS | Scalable Gaussian Process Inference with Finite-data Mean and Variance Guarantees. | Jonathan H. Huggins, Trevor Campbell, Mikolaj J. Kasprzak, Tamara Broderick |
| 2018 | ICML | Bayesian Coreset Construction via Greedy Iterative Geodesic Ascent. | Trevor Campbell, Tamara Broderick |
| 2017 | CVPR | Efficient Global Point Cloud Alignment Using Bayesian Nonparametric Mixtures. | Julian Straub, Trevor Campbell, Jonathan P. How, John W. Fisher III |
| 2015 | CVPR | Small-variance nonparametric clustering on the hypersphere. | Julian Straub, Trevor Campbell, Jonathan P. How, John W. Fisher III |
| 2014 | UAI | Approximate Decentralized Bayesian Inference. | Trevor Campbell, Jonathan P. How |