Clayton T Morrison

Interests

Research

Machine Learning, Causal Inference, Artificial Intelligence, Automated Planning, Knowledge Representation, Cognitive Science

Courses

Scholarly Contributions

Journals/Publications

• Noriega-Atala, E., Hein, P. D., Thumsi, S. S., Wong, Z., Wang, X., Hendryx, S., & Morrison, C. T. (2019). Inter-sentence Relation Extraction for Associating Biological Context with Events in Biomedical Texts. IEEE/ACM Transactions of Computational Biology and Bioinformatics (TCBB).
• Savage, R., Palafox, L. F., Morrison, C. T., Rodriguez, J. J., Barnard, K. J., Byrne, S., & Hamilton, C. W. (2018). A Bayesian Approach to Sub-Kilometer Crater Shape Analysis using Individual HiRISE Images. IEEE Transactions on Geoscience and Remote Sensing, PP(99), 1-11. doi:10.1109/TGRS.2018.2825608
• Valenzuela-Escárcega, M. A., Babur, Ö., Hahn-Powell, G., Bell, D., Hicks, T., Noriega-Atala, E., Wang, X., Surdeanu, M., Demir, E., & Morrison, C. T. (2018). Large-scale Automated Reading with Reach Discovers New Cancer Driving Mechanisms. Database: The Journal of Biological Databases and Curation.
• Camillo Villegas, J., Espeleta, J. E., Morrison, C. T., Breshears, D. D., & Huxman, T. E. (2014). Factoring in canopy cover heterogeneity on evapotranspiration partitioning: Beyond big-leaf surface homogeneity assumptions. Journal of Soil and Water Conservation, 69(3), 78A-83A.

Proceedings Publications

• Noriega-Atala, E., Liang, Z., Bachman, J., Morrison, C. T., & Surdeanu, M. (2019, Summer). Understanding the Polarities of Events in the Biomedical Literature: Deep Learning vs. Linguistically-informed Methods. In Workshop on Extracting Structured Knowledge from Scientific Publications (ESSP).
• Pyarelal, A., Sharp, R., Morrison, C. T., & Barnard, J. J. (2019, May). Interpreting Causal Expressions with Gradable Adjectives to Assembly Dynamics Models. In Modeling the World's Systems.
• Pyarelal, A., Valenzuela-Escárcega, M. A., Sharp, R., Hein, P. D., Stephens, J., Bhandari, P., Lim, H., Debray, S., & Morrison, C. T. (2019, May). AutoMATES: Automated Model Assembly from Text, Equations, and Software. In Modeling the World's Systems.
  More info

  Models of complicated systems can be represented in different ways - inscientific papers, they are represented using natural language text as well asequations. But to be of real use, they must also be implemented as software,thus making code a third form of representing models. We introduce theAutoMATES project, which aims to build semantically-rich unifiedrepresentations of models from scientific code and publications to facilitatethe integration of computational models from different domains and allow formodeling large, complicated systems that span multiple domains and levels ofabstraction.
• Sharp, R., Pyarelal, A., Gyori, B. M., Alcock, K., Laparra, E., Valenzuela-Escárcega, M. A., Nagesh, A., Yadav, V., Bachman, J. A., Tang, Z., Lent, H., Luo, F., Paul, M., Bethard, S. J., Barnard, J. J., Morrison, C. T., & Surdeanu, M. (2019, Summer). Eidos, INDRA & Delphi: From Free Text to Executable Causal Models. In Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL).
• Jansen, P. A., Wainwright, E., Marmorstein, S., & Morrison, C. T. (2018, May). WorldTree: A Corpus of Explanation Graphs for Elementary Science Questions supporting Multi-hop Inference. In Language Resources and Evaluation Conference (LREC).
• Noriega-Atala, E., Hein, P. D., Thumsi, S. S., Wong, Z., Wang, X., & Morrison, C. T. (2018, September). Inter-sentence Relation Extraction for Associating Biological Context with Events in Biomedical Texts. In The Sixth Workshop on Data Mining in Biomedical Informatics and Healthcare, held in conjunction with the IEEE International Conference on Data Mining (DMBIH@ICDM’18).
• Dawson, C. R., Huang, C., & Morrison, C. T. (2017, August). An infinite hidden Markov model with similarity-based transitions. In The Thirty-Fourth International Conference on Machine Learning (ICML 2017).
  More info

  Short paper at competitive conference, double-blind review with acceptance rate of 25.46% (433 accepted out of 1701 submissions)
• Noriega-Atala, E., Valenzuela-Escárcega, M. A., Morrison, C. T., & Surdeanu, M. (2017, August). Focused Reading: Reinforcement Learning for What Documents to Read. In ICML 2017 Workshop on Interactive Machine Learning and Semantic Information Retrieval (IMLSIR@ICML 2017).
• Noriega-Atala, E., Valenzuela-Escárcega, M. A., Morrison, C. T., & Surdeanu, M. (2017, September). Learning what to read: Focused machine reading. In Conference on Empirical Methods in Natural Language Processing (EMNLP 2017).
  More info

  Short paper at competitive conference, double-blind review with acceptance rate of 18% (107 accepted out of 582 submissions)
• Quick, D., & Morrison, C. T. (2017, October). Composition by Conversation. In The Forty-Third International Computer Music Conference (ICMC 2017).
  More info

  Full paper at competitive conference, double-blind review.
• Valenzuela-Escárcega, M. A., Babur, Ö., Hahn-Powell, G., Bell, D., Hicks, T., Noriega-Atala, E., Wang, X., Surdeanu, M., Demir, E., & Morrison, C. T. (2017, September). Large-scale Automated Reading with Reach Discovers New Cancer Driving Mechanisms. In BioCreative VI Workshop (BioCreative6 2017).
• Brau, E., Dawson, C. R., Carillo, A., Sidi, D., & Morrison, C. T. (2016, February). Bayesian inference of recursive sequences of group activities from tracks. In The Thirteenth AAAI Conference on Artificial Intelligence (AAAI 2016).
  More info

  Full paper at competitive conference, double-blind review with acceptance rate of 26% (549 accepted out of 2132 submissions)
• Gorji-Sefidmazgi, M., & Morrison, C. T. (2016, September). Spatiotemporal analysis of seasonal precipitation over US using co-clustering. In The 6th International Workshop on Climate Informatics (IC 2016).
• Shiaun Peng, K., & Morrison, C. T. (2016, July). Model predictive prior reinforcement learning for a heat pump thermostat. In The 11th International Workshop on Feedback Computing (FC 2016).
• Dykhuis, N. J., Rossi, F., & Morrison, C. T. (2015, June). Contributions to Teams Formed in Dynamic Networks. In The Multi-disciplinary Conference on Reinforcement Learning and Decision Making (RLDM 2015).
• Guan, J., Brau, E., Simek, K., Morrison, C. T., Butler, E. A., & Barnard, K. J. (2015, July). Moderated and Drifting Linear Dynamical Systems. In International Conference on Machine Learning (ICML 2015).
  More info

  This venue is a peer reviewed, competitive conference (acceptance rate: 26%) and the full paper is published as part of the conference proceedings
• Guan, J., Brau, E., Simek, K., Morrison, C. T., Butler, E. A., & Barnard, K. J. (2015, July). Moderated and Drifting Linear Dynamical Systems. In International Conference on Machine Learning.
  More info

  This venue is a peer reviewed, competitive conference (acceptance rate: 26%) and the full paper is published as part of the conference proceedings [ CSRanking endorsed, A* ]
• Hamilton, C. W., Palafox, L. F., & Morrison, C. T. (2015, June-July). Automated detection of geologic changes on Mars using Bayesian models. In International Union of Geodesy and Geophysics, General Assembly, 26.

Poster Presentations

• Hoogenboom, G., Morrison, C. T., Porter, C., Hein, P. D., & Pyarelal, A. (2020, Spring). Tools to Support Computational Crop Model Analysis and Comparison. The Second International Crop Modeling Symposium (iCROPM).
• Dudding, K. M., Carrington, J. M., & Morrison, C. T. (2019, Summer). Detecting Neonatal Pain Through the Connection of Neonate-Nurse Communication. Career, Connection, Community, Communicating Nursing Research. San Diego, CA.
• Hamilton, C. W., Palafox Novack, L. F., & Morrison, C. T. (2015, June-July). Automated detection of geologic changes on Mars using Bayesian models. The 26th General Assembly of the International Union of Geodesy and Geophysics (IUGG). Prague, the Czech Republic.