| Drug‐drug interaction discovery: kernel learning from heterogeneous similarities DS Dhami, G Kunapuli, M Das, D Page, S Natarajan Smart Health 9, 88-100, 2018 | 16 | 2018 |
| Fast relational probabilistic inference and learning: Approximate counting via hypergraphs M Das, DS Dhami, G Kunapuli, K Kersting, S Natarajan Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 7816-7824, 2019 | 11 | 2019 |
| Identifying parkinson’s patients: A functional gradient boosting approach DS Dhami, A Soni, D Page, S Natarajan Conference on Artificial Intelligence in Medicine in Europe, 332-337, 2017 | 10 | 2017 |
| Machine learning applications to resting-state functional MR imaging analysis JM Billings, M Eder, WC Flood, DS Dhami, S Natarajan, CT Whitlow Neuroimaging Clinics 27 (4), 609-620, 2017 | 8 | 2017 |
| Morphological classification of galaxies into spirals and non-spirals DS Dhami Indiana University, 2015 | 3 | 2015 |
| Human-Guided Learning of Column Networks: Knowledge Injection for Relational Deep Learning M Das, DS Dhami, Y Yu, G Kunapuli, S Natarajan 8th ACM IKDD CODS and 26th COMAD, 110-118, 2021 | 2* | 2021 |
| Non-parametric learning of gaifman models DS Dhami, S Yan, G Kunapuli, S Natarajan arXiv preprint arXiv:2001.00528, 2020 | 2 | 2020 |
| Predicting drug-drug interactions from molecular structure images DS Dhami, G Kunapuli, D Page, S Natarajan AAAI Fall Symposium on AI for Social Good, 2019 | 1 | 2019 |
| Knowledge-based morphological classification of galaxies from vision features DS Dhami, D Leake, S Natarajan Workshops at the thirty-first AAAI conference on artificial intelligence, 2017 | 1 | 2017 |
| Predicting Drug-Drug Interactions from Heterogeneous Data: An Embedding Approach DS Dhami, S Yan, G Kunapuli, D Page, S Natarajan International Conference on Artificial Intelligence in Medicine, 252-257, 2021 | | 2021 |
| Intriguing Parameters of Structural Causal Models M Zečević, DS Dhami, K Kersting arXiv preprint arXiv:2105.12697, 2021 | | 2021 |
| Interventional Sum-Product Networks: Causal Inference with Tractable Probabilistic Models M Zečević, DS Dhami, A Karanam, S Natarajan, K Kersting arXiv preprint arXiv:2102.10440, 2021 | | 2021 |
| Bridging Graph Neural Networks and Statistical Relational Learning: Relational One-Class GCN DS Dhami, S Yan, S Natarajan arXiv preprint arXiv:2102.07007, 2021 | | 2021 |
| The Curious Case of Stacking Boosted Relational Dependency Networks S Yan, DS Dhami, S Natarajan ''I Can't Believe It's Not Better!''NeurIPS 2020 workshop, 2020 | | 2020 |
| Knowledge Intensive Learning of Generative Adversarial Networks DS Dhami, M Das, S Natarajan KiML@ KDD, 2020 | | 2020 |
| Effective Learning with Heterogenous, Noisy, Multi-Relational Healthcare Data DS Dhami | | 2020 |
| Extraction of Morphological features of Galaxies using Computer Vision Methods C Achgill, DS Dhami, T Alowaiseq | | |
| Morphological Classification of Galaxies based on Computer Vision features using CBR and Rule Based Systems DS Dhami, T Alowaisheq | | |
| Approximate Counting for Fast Inference and Learning in Probabilistic Programming M Das, DS Dhami, G Kunapuli, K Kersting, S Natarajan | | |
| Predicting Drug-Drug Interactions from Text using NLP and Privileged Information AL Hayes, S Smith, DS Dhami, S Natarajan | | |
Sriraam NatarajanUniversity of Texas at DallasGeverifieerd e-mailadres voor utdallas.edu
