| Systems and methods for deep model translation generation JP Kaufhold, JA Sleeman US Patent 10,504,004, 2019 | 60 | 2019 |
| Robust semantic text similarity using LSA, machine learning, and linguistic resources A Kashyap, L Han, R Yus, J Sleeman, T Satyapanich, S Gandhi, T Finin Language Resources and Evaluation 50, 125-161, 2016 | 55 | 2016 |
| Type prediction for efficient coreference resolution in heterogeneous semantic graphs J Sleeman, T Finin 2013 IEEE Seventh International Conference on Semantic Computing, 78-85, 2013 | 45 | 2013 |
| Topic modeling for RDF graphs J Sleeman, T Finin, A Joshi 3rd International Workshop on Linked Data for Information Extraction, 14th …, 2015 | 44 | 2015 |
| Meerkat mafia: Multilingual and cross-level semantic textual similarity systems AL Kashyap, L Han, R Yus, J Sleeman, TW Satyapanich, SR Gandhi, ... Proceedings of the 8th International Workshop on Semantic Evaluation, 416-423, 2014 | 40 | 2014 |
| Entity type recognition for heterogeneous semantic graphs J Sleeman, T Finin, A Joshi AI Magazine 36 (1), 75-86, 2015 | 37 | 2015 |
| Computing foaf co-reference relations with rules and machine learning J Sleeman, T Finin Proceedings of the Third International Workshop on Social Data on the Web at …, 2010 | 32 | 2010 |
| A hybrid quantum enabled RBM advantage: convolutional autoencoders for quantum image compression and generative learning J Sleeman, J Dorband, M Halem Quantum information science, sensing, and computation XII 11391, 23-38, 2020 | 27 | 2020 |
| A Machine Learning Approach to Linking FOAF Instances. J Sleeman, T Finin AAAI Spring Symposium: Linked Data Meets Artificial Intelligence, 2010 | 19 | 2010 |
| A deep machine learning approach for lidar based boundary layer height detection J Sleeman, M Halem, Z Yang, V Caicedo, B Demoz, R Delgado IGARSS 2020-2020 IEEE international geoscience and remote sensing symposium …, 2020 | 17 | 2020 |
| Understanding cybersecurity threat trends through dynamic topic modeling J Sleeman, T Finin, M Halem Frontiers in big Data 4, 601529, 2021 | 14 | 2021 |
| Learning co-reference relations for FOAF instances J Sleeman, T Finin Proceedings of the Poster and Demonstration Session at the 9th International …, 2010 | 12 | 2010 |
| Modeling the Evolution of Climate Change Assessment Research Using Dynamic Topic Models and Cross-Domain Divergence Maps. J Sleeman, M Halem, T Finin, M Cane AAAI Spring Symposia, 2017 | 11 | 2017 |
| Real-time path planning for a robotic arm K Krishnaswamy, J Sleeman, T Oates Proceedings of the 4th International Conference on Pervasive Technologies …, 2011 | 11 | 2011 |
| Ontology-grounded topic modeling for climate science research J Sleeman, T Finin, M Halem Emerging Topics in Semantic Technologies, 191-202, 2018 | 10 | 2018 |
| Dynamic topic modeling to infer the influence of research citations on ipcc assessment reports J Sleeman, M Halem, T Finin, M Cane Big data challenges, research, and technologies in the earth and planetary …, 2016 | 9 | 2016 |
| Temporal understanding of cybersecurity threats J Sleeman, T Finin, M Halem 2020 IEEE 6th Intl Conference on Big Data Security on Cloud (BigDataSecurity …, 2020 | 7 | 2020 |
| A generative adversarial network for climate tipping point discovery (tip-gan) J Sleeman, D Chung, A Gnanadesikan, J Brett, Y Kevrekidis, M Hughes, ... arXiv preprint arXiv:2302.10274, 2023 | 6 | 2023 |
| Fine and ultra-fine entity type embeddings for question answering S Vallurupalli, J Sleeman, T Finin International Semantic Web Conference, 2020 | 6 | 2020 |
| Discovering scientific influence using cross-domain dynamic topic modeling J Sleeman, M Halem, T Finin, M Cane 2017 IEEE international conference on big data (big data), 1325-1332, 2017 | 6 | 2017 |
Tim FininUniversity of Maryland, Baltimore CountyVerified email at umbc.edu
