| 2016 | KDD | Scalable Data Analytics Using R: Single Machines to Hadoop Spark Clusters. | John Mark Agosta, Debraj GuhaThakurta, Robert Horton, Mario Inchiosa, Srini Kumar, Mengyue Zhao |
| 2013 | INFOCOM | Mixture models of endhost network traffic. | John Mark Agosta, Jaideep Chandrashekar, Mark Crovella, Nina Taft, Daniel Ting |
| 2013 | UAI | A Lightweight Inference Method for Image Classification. | John Mark Agosta, Preeti J. Pillai |
| 2010 | WWW | What is disputed on the web? | Rob Ennals, Dan Byler, John Mark Agosta, Barbara Rosario |
| 2010 | WWW | Highlighting disputed claims on the web. | Rob Ennals, Beth Trushkowsky, John Mark Agosta |
| 2009 | ICML | Workshop summary: Seventh annual workshop on Bayes applications. | John Mark Agosta, Russell G. Almond, Dennis M. Buede, Marek J. Druzdzel, Judy Goldsmith, Silja Renooij |
| 2008 | RAID | Optimal Cost, Collaborative, and Distributed Response to Zero-Day Worms - A Control Theoretic Approach. | Senthilkumar G. Cheetancheri, John Mark Agosta, Karl N. Levitt, Shyhtsun Felix Wu, Jeff Rowe |
| 2006 | AAAI | When Gossip is Good: Distributed Probabilistic Inference for Detection of Slow Network Intrusions. | Denver Dash, Branislav Kveton, John Mark Agosta, Eve M. Schooler, Jaideep Chandrashekar, Abraham Bachrach, Alex Newman |
| 2006 | SIGCOMM | A distributed host-based worm detection system. | Senthilkumar G. Cheetancheri, John Mark Agosta, Denver Dash, Karl N. Levitt, Jeff Rowe, Eve M. Schooler |
| 1996 | UAI | Constraining Influence Diagram Structure by Generative Planning: An Application to the Optimization of Oil Spill Response. | John Mark Agosta |
| 1991 | UAI | "Conditional Inter-Causally Independent" Node Distributions, a Property of "Noisy-OR" Models. | John Mark Agosta |
| 1989 | UAI | Model-Based Influence Diagrams for Machine Vision. | Tod S. Levitt, John Mark Agosta, Thomas O. Binford |
| 1988 | UAI | The structure of bayes networks for visual recognition. | John Mark Agosta |