Discovering Latent Network Structure in Point Process Data. Linderman, SW, Adams RP.  Thirty-First International Conference on Machine Learning (ICML). 2014.   { arXiv:1402.0914 [stat.ML] | PDF | Google Scholar | BibTex }
Discovering Shared Cardiovascular Dynamics within a Patient Cohort. Nemati, S, Lehman L-wei, Adams RP, Malhotra A.  International Conference of the IEEE Engineering in Medicine and Biology Society. 2012.   { PDF | Google Scholar | BibTex }
Discovering Shared Dynamics in Physiological Signals: Application to Patient Monitoring in ICU. Lehman, L-wei, Nemati S, Adams RP, Mark R.  International Conference of the IEEE Engineering in Medicine and Biology Society. 2012.   { PDF | Google Scholar | BibTex }
Fast Exact Inference for Recursive Cardinality Models. Tarlow, D, Swersky K, Zemel RS, Adams RP, Frey B.  28th Conference on Uncertainty in Artificial Intelligence (UAI). 2012.   { PDF | Google Scholar | BibTex }
Firefly Monte Carlo: Exact MCMC with Subsets of Data. Maclaurin, D, Adams RP.  Thirtieth Conference on Uncertainty in Artificial Intelligence (UAI). 2014.   { arXiv:1403.5693 [stat.ML] | PDF | Google Scholar | BibTex } Winner of Best Paper Award
The Gaussian Process Density Sampler. Adams, RP, Murray I, MacKay DJC.  Advances in Neural Information Processing Systems 21. 2009.   { PDF | Google Scholar | BibTex }
Gaussian Process Kernels for Pattern Discovery and Extrapolation. Wilson, AG, Adams RP.  Proceedings of the 30th International Conference on Machine Learning. 2013.   { arXiv:1302.4245 [stat.ML] | PDF | Code | Google Scholar | BibTex }
Gaussian Process Product Models for Nonparametric Nonstationarity. Adams, RP, Stegle O.  Proceedings of the 25th International Conference on Machine Learning. 1-8. 2008.   { PDF | Google Scholar | BibTex }
Graph-Sparse LDA: A Topic Model with Structured Sparsity. Doshi-Velez, F, Wallace B, Adams RP.  Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence. Submitted.   { arXiv:1410.4510 [stat.ML] | PDF | Google Scholar | BibTex }
Learning Ordered Representations with Nested Dropout. Rippel, O, Gelbart MA, Adams RP.  Thirty-First International Conference on Machine Learning (ICML). 2014.   { arXiv:1402.0915 [stat.ML] | PDF | Google Scholar | BibTex }
Learning Outcome-Discriminative Dynamics in Multivariate Physiological Cohort Time Series. Nemati, S, Lehman L-wei, Adams RP.  Proceedings of the 35th International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) . 2013.   { PDF | Google Scholar | BibTex }
Learning the Parameters of Determinantal Point Process Kernels. Affandi, RH, Fox EB, Adams RP, Taskar B.  Thirty-First International Conference on Machine Learning (ICML). 2014.   { arXiv:1402.4862 [stat.ML] | PDF | Google Scholar | BibTex }
Message Passing Inference with Chemical Reaction Networks. Napp, N, Adams RP.  Advances in Neural Information Processing Systems 26. 2013.   { PDF | Google Scholar | BibTex }
Multi-Task Bayesian Optimization. Swersky, K, Snoek J, Adams RP.  Advances in Neural Information Processing Systems 26. 2013.   { PDF | Code | Google Scholar | BibTex }
On Nonparametric Guidance for Learning Autoencoder Representations. Snoek, J, Adams RP, Larochelle H.  Fifteenth International Conference on Artificial Intelligence and Statistics (AISTATS). 2012.   { arXiv:1102.1492v4 [stat.ML] | PDF | Code | Google Scholar | BibTex }