Johnson, Matthew J.
- Composing graphical models with neural networks for structured representations and fast inference
2016/03/20 by Matthew Johnson, Johnson, Matthew J., David Duvenaud +7 · 24 citations
Computer Science · #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (stat.ML) #Neural Networks and Applications #Time Series Analysis and Forecasting
- Dependent Multinomial Models Made Easy: Stick Breaking with the Pólya-Gamma Augmentation
2015/06/18 by Linderman, Scott W., Johnson, Matthew J., Adams, Ryan P. · 3 citations
#FOS: Computer and information sciences #Machine Learning (stat.ML)
- Recurrent switching linear dynamical systems
2016/10/26 by Scott W. Linderman, Andrew C. Miller, Linderman, Scott W. +9 · 3 citations
Computer Science · Engineering · #Control Systems and Identification #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (stat.ML) #Time Series Analysis and Forecasting
- Estimating the Spectral Density of Large Implicit Matrices
2018/02/09 by Adams, Ryan P., Pennington, Jeffrey, Johnson, Matthew J. +4 · 2 citations
#Computation (stat.CO) #FOS: Computer and information sciences #Machine Learning (stat.ML)
- Autoconj: Recognizing and Exploiting Conjugacy Without a Domain-Specific Language
2018/11/29 by Hoffman, Matthew D., Johnson, Matthew J., Tran, Dustin · 1 citation
#FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Programming Languages (cs.PL)
- Multimodal Prediction and Personalization of Photo Edits with Deep Generative Models
2017/04/17 by Ardavan Saeedi, Saeedi, Ardavan, Matthew D. Hoffman +9 · 1 citation
Computer Science · #Advanced Image and Video Retrieval Techniques #FOS: Computer and information sciences #Generative Adversarial Networks and Image Synthesis #Image Retrieval and Classification Techniques #Machine Learning (cs.LG) #Machine Learning (stat.ML)