Matthew J. Johnson
According to our database1, Matthew J. Johnson authored at least 14 papers between 2010 and 2018.
Legend:Book In proceedings Article PhD thesis Other
Multimodal Prediction and Personalization of Photo Edits with Deep Generative Models.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018
Structure-Exploiting variational inference for recurrent switching linear dynamical systems.
Proceedings of the 2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2017
Bayesian Learning and Inference in Recurrent Switching Linear Dynamical Systems.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017
Cross-Corpora Unsupervised Learning of Trajectories in Autism Spectrum Disorders.
Journal of Machine Learning Research, 2016
Patterns of Scalable Bayesian Inference.
Foundations and Trends in Machine Learning, 2016
Composing graphical models with neural networks for structured representations and fast inference.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016
The Segmented iHMM: A Simple, Efficient Hierarchical Infinite HMM.
Proceedings of the 33nd International Conference on Machine Learning, 2016
Dependent Multinomial Models Made Easy: Stick-Breaking with the Polya-gamma Augmentation.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015
Bayesian time series models and scalable inference.
PhD thesis, 2014
Stochastic Variational Inference for Bayesian Time Series Models.
Proceedings of the 31th International Conference on Machine Learning, 2014
Bayesian nonparametric hidden semi-Markov models.
Journal of Machine Learning Research, 2013
Analyzing Hogwild Parallel Gaussian Gibbs Sampling.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013
The Hierarchical Dirichlet Process Hidden Semi-Markov Model.
Proceedings of the UAI 2010, 2010
Necessary and sufficient conditions for high-dimensional salient feature subset recovery.
Proceedings of the IEEE International Symposium on Information Theory, 2010