Trevor Campbell

发表

Slice Sampling for General Completely Random Measures pdf

Peiyuan Zhu, Alexandre Bouchard-Cot'e, Trevor Campbell, 2020, UAI.

Bayesian Pseudocoresets

Trevor Campbell, Dionysis Manousakas, Zuheng Xu, 2020, Neural Information Processing Systems.

Universal Boosting Variational Inference

Trevor Campbell, Xinglong Li, 2019, NeurIPS.

Scalable Gaussian Process Inference with Finite-data Mean and Variance Guarantees

Trevor Campbell, Tamara Broderick, Jonathan H. Huggins, 2018, AISTATS.

Efficient Global Point Cloud Alignment Using Bayesian Nonparametric Mixtures

Jonathan P. How, John W. Fisher, Trevor Campbell, 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

Efficient Globally Optimal Point Cloud Alignment using Bayesian Nonparametric Mixtures pdf

Jonathan P. How, John W. Fisher, Trevor Campbell, 2016, ArXiv.

Coresets for Scalable Bayesian Logistic Regression

Trevor Campbell, Tamara Broderick, Jonathan H. Huggins, 2016, NIPS.

Edge-exchangeable graphs and sparsity

Trevor Campbell, Tamara Broderick, Diana Cai, 2016, NIPS.

Small-variance nonparametric clustering on the hypersphere

Jonathan P. How, John W. Fisher, Trevor Campbell, 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

Validated Variational Inference via Practical Posterior Error Bounds

Trevor Campbell, Tamara Broderick, Jonathan H. Huggins, 2019, AISTATS.

Multiagent planning with Bayesian nonparametric asymptotics

Trevor Campbell, Trevor Campbell, 2013 .

Planning under Uncertainty using Bayesian Nonparametric Models

Sameera S. Ponda, Jonathan P. How, Girish Chowdhary, 2012 .

Automated Scalable Bayesian Inference via Hilbert Coresets

Trevor Campbell, Tamara Broderick, Tamara Broderick, 2017, J. Mach. Learn. Res..

Reconstructing probabilistic trees of cellular differentiation from single-cell RNA-seq data pdf

Trevor Campbell, William T. Stephenson, Tamara Broderick, 2018, ArXiv.

Bayesian Coreset Construction via Greedy Iterative Geodesic Ascent pdf

Trevor Campbell, Tamara Broderick, Tamara Broderick, 2018, ICML.

Dynamic Clustering Algorithms via Small-Variance Analysis of Markov Chain Mixture Models

Trevor Campbell, Brian Kulis, Jonathan How, 2017, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Patrick Edward Dunne, 1930-2011

Trevor Campbell, Trevor Campbell, 2011 .

Data-dependent compression of random features for large-scale kernel approximation

Trevor Campbell, Tamara Broderick, Raj Agrawal, 2019, AISTATS.

Multiagent allocation of Markov decision process tasks

Luke B. Johnson, Jonathan P. How, Trevor Campbell, 2013, 2013 American Control Conference.

Sparse Variational Inference: Bayesian Coresets from Scratch pdf

Trevor Campbell, Boyan Beronov, Trevor Campbell, 2019, NeurIPS.

Practical bounds on the error of Bayesian posterior approximations: A nonasymptotic approach pdf

Trevor Campbell, Tamara Broderick, Jonathan H. Huggins, 2018, ArXiv.

Streaming, Distributed Variational Inference for Bayesian Nonparametrics

Jonathan P. How, John W. Fisher, Trevor Campbell, 2015, NIPS.

Physics-Informed Neural Network for Modelling the Thermochemical Curing Process of Composite-Tool Systems During Manufacture pdf

Trevor Campbell, Reza Vaziri, Ehsan Haghighat, 2020, ArXiv.

Bayesian nonparametric set construction for robust optimization

Jonathan P. How, Trevor Campbell, J. How, 2015, 2015 American Control Conference (ACC).

Practical Posterior Error Bounds from Variational Objectives pdf

Trevor Campbell, Tamara Broderick, Jonathan H. Huggins, 2019, ArXiv.

Approximate Decentralized Bayesian Inference

Jonathan P. How, Trevor Campbell, J. How, 2014, UAI.

Dynamic Clustering via Asymptotics of the Dependent Dirichlet Process Mixture

Jonathan P. How, Lawrence Carin, Trevor Campbell, 2013, NIPS.

Planning under Uncertainty using Nonparametric Bayesian Models

Sameera S. Ponda, Jonathan P. How, Girish Chowdhary, 2012 .

Truncated simulation and inference in edge-exchangeable networks

Trevor Campbell, Xinglong Li, 2021, Electronic Journal of Statistics.

Parallel tempering on optimized paths

Trevor Campbell, Saifuddin Syed, Vittorio Romaniello, 2021, ICML.

Sequential core-set Monte Carlo

Trevor Campbell, Frank Wood, Christian Weilbach, 2021, UAI.

Pseudo-Marginal Inference for CTMCs on Infinite Spaces via Monotonic Likelihood Approximations

Trevor Campbell, Alexandre Bouchard-Cot'e, Miguel Biron-Lattes, 2021, J. Comput. Graph. Stat..

Finite mixture models do not reliably learn the number of components

Trevor Campbell, Tamara Broderick, Diana Cai, 2020, International Conference on Machine Learning.