Publications (38)
GEMSEC: Graph Embedding with Self Clustering
Benedek Rozemberczki, Ryan Davies, Rik Sarkar +1
Latent Bayesian melding for integrating individual and population models
Mingjun Zhong, Nigel Goddard, Charles Sutton
Semi-Separable Hamiltonian Monte Carlo for Inference in Bayesian Hierarchical Models
Yichuan Zhang, Charles Sutton
Capturing Data Uncertainty in High-Volume Stream Processing
Yanlei Diao, Boduo Li, Anna Liu +4
Bayesian inference for queueing networks and modeling of internet services
Charles Sutton, Michael I. Jordan
Deep Learning to Detect Redundant Method Comments
Annie Louis, Santanu Kumar Dash, Earl T. Barr +1
Mining Idioms from Source Code
Miltiadis Allamanis, Charles Sutton
Autofolding for Source Code Summarization
Jaroslav Fowkes, Pankajan Chanthirasegaran, Razvan Ranca +3
HOUDINI: Lifelong Learning as Program Synthesis
Lazar Valkov, Dipak Chaudhari, Akash Srivastava +2
Piecewise Training for Undirected Models
Charles Sutton, Andrew McCallum
Clustering with a Reject Option: Interactive Clustering as Bayesian Prior Elicitation
Akash Srivastava, James Zou, Ryan P. Adams +1
Distributed Inference and Query Processing for RFID Tracking and Monitoring
Zhao Cao, Charles Sutton, Yanlei Diao +1
Maybe Deep Neural Networks are the Best Choice for Modeling Source Code
Rafael-Michael Karampatsis, Charles Sutton
Tailored Mutants Fit Bugs Better
Miltiadis Allamanis, Earl T. Barr, René Just +1
Wrangling Messy CSV Files by Detecting Row and Type Patterns
Gerrit J. J. van den Burg, Alfredo Nazabal, Charles Sutton
VEEGAN: Reducing Mode Collapse in GANs using Implicit Variational Learning
Akash Srivastava, Lazar Valkov, Chris Russell +2
Interpreting Deep Classifier by Visual Distillation of Dark Knowledge
Kai Xu, Dae Hoon Park, Chang Yi +1
Learning Semantic Annotations for Tabular Data
Jiaoyan Chen, Ernesto Jimenez-Ruiz, Ian Horrocks +1
A Survey of Machine Learning for Big Code and Naturalness
Miltiadis Allamanis, Earl T. Barr, Premkumar Devanbu +1
Learning Natural Coding Conventions
Miltiadis Allamanis, Earl T. Barr, Christian Bird +1
Interleaved Factorial Non-Homogeneous Hidden Markov Models for Energy Disaggregation
Mingjun Zhong, Nigel Goddard, Charles Sutton
Scheduled denoising autoencoders
Krzysztof J. Geras, Charles Sutton
Autoencoding Variational Inference For Topic Models
Akash Srivastava, Charles Sutton
Clustering with a Reject Option: Interactive Clustering as Bayesian Prior Elicitation
Akash Srivastava, James Zou, Charles Sutton
A Subsequence Interleaving Model for Sequential Pattern Mining
Jaroslav Fowkes, Charles Sutton
Learning Continuous Semantic Representations of Symbolic Expressions
Miltiadis Allamanis, Pankajan Chanthirasegaran, Pushmeet Kohli +1
Improved Dynamic Schedules for Belief Propagation
Charles Sutton, Andrew McCallum
Variational Inference In Pachinko Allocation Machines
Akash Srivastava, Charles Sutton
Popularity of arXiv.org within Computer Science
Charles Sutton, Linan Gong
A Bayesian Network Model for Interesting Itemsets
Jaroslav Fowkes, Charles Sutton
Blending LSTMs into CNNs
Krzysztof J. Geras, Abdel-rahman Mohamed, Rich Caruana +6
Sequence-to-point learning with neural networks for nonintrusive load monitoring
Chaoyun Zhang, Mingjun Zhong, Zongzuo Wang +2
ColNet: Embedding the Semantics of Web Tables for Column Type Prediction
Jiaoyan Chen, Ernesto Jimenez-Ruiz, Ian Horrocks +1
Word Storms: Multiples of Word Clouds for Visual Comparison of Documents
Quim Castella, Charles Sutton
An Introduction to Conditional Random Fields
Charles Sutton, Andrew McCallum
Probabilistic Programming with Densities in SlicStan: Efficient, Flexible and Deterministic
Maria I. Gorinova, Andrew D. Gordon, Charles Sutton
A Convolutional Attention Network for Extreme Summarization of Source Code
Miltiadis Allamanis, Hao Peng, Charles Sutton
Parameter-Free Probabilistic API Mining across GitHub
Jaroslav Fowkes, Charles Sutton