Benjamin M Marlin

Benjamin M Marlin, M. Pavel, D. Spruijt-Metz, 2022, 2022 IEEE/ACM Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE).

Cider

Benjamin M Marlin, Deepak Ganesan, Pan Hu, 2015, Food, Fermentation, and Micro-organisms.

Conditional random fields for morphological analysis of wireless ECG signals

Deepak Ganesan, Benjamin M. Marlin, Annamalai Natarajan, 2014, BCB.

Learning Time Series Detection Models from Temporally Imprecise Labels

Benjamin M. Marlin, Roy J. Adams, Benjamin M Marlin, 2016, AISTATS.

Missing Data Problems in Machine Learning

Benjamin M. Marlin, Benjamin M Marlin, 2008 .

Eurographics Symposium on Geometry Processing 2015 Analysis and Synthesis of 3d Shape Families via Deep-learned Generative Models of Surfaces

Evangelos Kalogerakis, Benjamin M. Marlin, Haibin Huang, 2022 .

MisGAN: Learning from Incomplete Data with Generative Adversarial Networks pdf

Bo Jiang, Benjamin M. Marlin, Benjamin M Marlin, 2019, ICLR.

A Survey on Principles, Models and Methods for Learning from Irregularly Sampled Time Series: From Discretization to Attention and Invariance pdf

Satya Narayan Shukla, Benjamin M. Marlin, Benjamin M Marlin, 2020, ArXiv.

Digitizing clinical trials

Benjamin M Marlin, R. Califf, P. Klasnja, 2020, npj Digital Medicine.

Hierarchical Span-Based Conditional Random Fields for Labeling and Segmenting Events in Wearable Sensor Data Streams

Abhinav Parate, Benjamin M. Marlin, Edison Thomaz, 2016, ICML.

puffMarker: a multi-sensor approach for pinpointing the timing of first lapse in smoking cessation

Emre Ertin, Mustafa al'Absi, Santosh Kumar, 2015, UbiComp.

Domain adaptation methods for improving lab-to-field generalization of cocaine detection using wearable ECG

Deepak Ganesan, Benjamin M. Marlin, Annamalai Natarajan, 2016, UbiComp.

Detecting cocaine use with wearable electrocardiogram sensors

Abhinav Parate, Deepak Ganesan, Annamalai Natarajan, 2013, UbiComp.

Center of Excellence for Mobile Sensor Data-to-Knowledge (MD2K).

Deborah Estrin, James M. Rehg, Gregory D. Abowd, 2017, IEEE pervasive computing.

Center of excellence for mobile sensor data-to-knowledge (MD2K)

Deborah Estrin, James M. Rehg, Gregory D. Abowd, 2015, J. Am. Medical Informatics Assoc..

Relation Extraction with Matrix Factorization and Universal Schemas

Andrew McCallum, Benjamin M. Marlin, Sebastian Riedel, 2013, NAACL.

Advancing Behavioral Intervention and Theory Development for Mobile Health: The HeartSteps II Protocol

Benjamin M Marlin, M. Pavel, D. Spruijt-Metz, 2022, International journal of environmental research and public health.

Unsupervised pattern discovery in electronic health care data using probabilistic clustering models

Benjamin M. Marlin, David C. Kale, Randall C. Wetzel, 2012, IHI '12.

Collaborative prediction and ranking with non-random missing data

Richard S. Zemel, Benjamin M. Marlin, Benjamin M Marlin, 2009, RecSys '09.

Generalized Bayesian Posterior Expectation Distillation for Deep Neural Networks

Benjamin M. Marlin, Borhan Jalaeian, Meet P. Vadera, 2020, UAI.

Digitizing clinical trials.

Benjamin M Marlin, R. Califf, P. Klasnja, 2020, NPJ digital medicine.

Learning from Irregularly-Sampled Time Series: A Missing Data Perspective

Benjamin M. Marlin, Benjamin M Marlin, Steven Cheng-Xian Li, 2020, ICML.

Interpolation-Prediction Networks for Irregularly Sampled Time Series pdf

Satya Narayan Shukla, Benjamin M. Marlin, Benjamin M Marlin, 2019, ICLR.

A tutorial on stochastic approximation algorithms for training Restricted Boltzmann Machines and Deep Belief Nets

Nando de Freitas, Bo Chen, Benjamin M. Marlin, 2010, 2010 Information Theory and Applications Workshop (ITA).

Impact of Parameter Sparsity on Stochastic Gradient MCMC Methods for Bayesian Deep Learning

Adam D. Cobb, Meet P. Vadera, Benjamin M Marlin, 2022, ArXiv.

Time Phased Manpower Model for Education Planning in Afghanistan.

Benjamin M Marlin, Hansuk Sohn, 2014 .

Inductive Principles for Restricted Boltzmann Machine Learning

Nando de Freitas, Bo Chen, Benjamin M. Marlin, 2010, AISTATS.

Collaborative Filtering and the Missing at Random Assumption pdf

Richard S. Zemel, Benjamin M. Marlin, Malcolm Slaney, 2007, UAI.

iLid: Low-power Sensing of Fatigue and Drowsiness Measures on a Computational Eyeglass

Deepak Ganesan, Benjamin M. Marlin, Jeremy Gummeson, 2017, Proc. ACM Interact. Mob. Wearable Ubiquitous Technol..

Toward an Internet of Battlefield Things: A Resilience Perspective

Paulo Tabuada, Suhas Diggavi, Ananthram Swami, 2018, Computer.

Active Collaborative Filtering pdf

Craig Boutilier, Richard S. Zemel, Benjamin M. Marlin, 2002, UAI.

A Stick-Breaking Likelihood for Categorical Data Analysis with Latent Gaussian Models

Mohammad Emtiyaz Khan, Kevin P. Murphy, Benjamin M. Marlin, 2012, AISTATS.

Practical prediction and prefetch for faster access to applications on mobile phones

David Chu, Abhinav Parate, Matthias Böhmer, 2013, UbiComp.

The ILHBN: challenges, opportunities, and solutions from harmonizing data under heterogeneous study designs, target populations, and measurement protocols

Timothy R. Brick, Benjamin M Marlin, D. Spruijt-Metz, 2022, Translational Behavioral Medicine.

BayesLDM: A Domain-specific Modeling Language for Probabilistic Modeling of Longitudinal Data

Benjamin M Marlin, D. Spruijt-Metz, Pedja Klasnja, 2022, 2022 IEEE/ACM Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE).

A scalable end-to-end Gaussian process adapter for irregularly sampled time series classification

Benjamin M. Marlin, Benjamin M Marlin, Steven Cheng-Xian Li, 2016, NIPS.

Will Distributed Computing Revolutionize Peace? The Emergence of Battlefield IoT

Paulo Tabuada, Suhas N. Diggavi, Gaurav S. Sukhatme, 2018, 2018 IEEE 38th International Conference on Distributed Computing Systems (ICDCS).

Post-hoc loss-calibration for Bayesian neural networks

Soumya Ghosh, Kenney Ng, Benjamin M. Marlin, 2021, UAI.

Interpolation-Prediction Networks for Irregularly Sampled Time Series

Satya Narayan Shukla, Benjamin M Marlin, 2019, ICLR.

Modeling Irregularly Sampled Clinical Time Series pdf

Satya Narayan Shukla, Benjamin M. Marlin, Benjamin M Marlin, 2018, ArXiv.

Inferring Smart Schedules for Dumb Thermostats

Prashant J. Shenoy, David E. Irwin, Srinivasan Iyengar, 2018, ACM Trans. Cyber Phys. Syst..

iProgram: Inferring Smart Schedules for Dumb Thermostats

Prashant J. Shenoy, David E. Irwin, Srinivasan Iyengar, 2015, BuildSys@SenSys.

The Shape-Time Random Field for Semantic Video Labeling

Benjamin M. Marlin, Erik G. Learned-Miller, Andrew Kae, 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.

Recommender Systems, Missing Data and Statistical Model Estimation

Richard S. Zemel, Benjamin M. Marlin, Malcolm Slaney, 2011, IJCAI.

Piecewise Bounds for Estimating Bernoulli-Logistic Latent Gaussian Models

Mohammad Emtiyaz Khan, Kevin P. Murphy, Benjamin M. Marlin, 2011, ICML.

Heteroscedastic Temporal Variational Autoencoder For Irregularly Sampled Time Series pdf

Satya Narayan Shukla, Benjamin M. Marlin, Benjamin M Marlin, 2021, ICLR.

Integrating Physiological Time Series and Clinical Notes with Deep Learning for Improved ICU Mortality Prediction pdf

Satya Narayan Shukla, Benjamin M. Marlin, Benjamin M Marlin, 2020, ArXiv.

Group Sparse Priors for Covariance Estimation

Mark W. Schmidt, Kevin P. Murphy, Benjamin M. Marlin, 2009, UAI.

Collective-Intelligence Recommender Systems: Advancing Computer Tailoring for Health Behavior Change Into the 21st Century

Rebecca L. Kinney, Benjamin M Marlin, S. Lemon, 2016, Journal of medical Internet research.

PERSPeCT: collaborative filtering for tailored health communications

Benjamin M. Marlin, Roy J. Adams, Thomas K. Houston, 2014, RecSys '14.

Towards Collaborative Filtering Recommender Systems for Tailored Health Communications

Benjamin M. Marlin, Roy J. Adams, Thomas K. Houston, 2013, AMIA.

Challenges and Opportunities in Approximate Bayesian Deep Learning for Intelligent IoT Systems pdf

Benjamin M. Marlin, Meet P. Vadera, Benjamin M Marlin, 2021, 2021 IEEE Third International Conference on Cognitive Machine Intelligence (CogMI).

iLid

Benjamin M Marlin, Deepak Ganesan, Jeremy Gummeson, 2017, Proc. ACM Interact. Mob. Wearable Ubiquitous Technol..

Center of Excellence for Mobile Sensor Data-to-Knowledge (MD2K)

James M. Rehg, Duen Horng Chau, Syed Monowar Hossain, 2017, IEEE Pervasive Computing.