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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
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Beyond Textual Data: Predicting Drug-Drug Interactions from Molecular Structure Images using Siamese Neural Networks
D. S. Dhami, S. Yan, G. Kunapuli, D. Page, S. Natarajan. 2020.
Non-Parametric Learning of Gaifman Models
D. S. Dhami, S. Yan, G. Kunapuli, S. Natarajan. Statistical Relational AI (StarAI) Workshop at AAAI 2020.
The Curious Case of Stacking Boosted Relational Dependency Networks
S. Yan, D. S. Dhami, S. Natarajan. Proceedings on I Cant Believe Its Not Better! at NeurIPS Workshops, PMLR 2020.
Predicting Drug-Drug Interactions from Heterogeneous Data: An Embedding Approach
D. S. Dhami*, S. Yan*, G. Kunapuli, D. Page, S. Natarajan. 19th International Conference in Artificial Intelligence in Medicine (AIME) 2021. (*=equal contribution)
Non-Parametric Learning of Embeddings for Relational Data using Gaifman Locality Theorem
D. S. Dhami, S. Yan, G. Kunapuli, S. Natarajan. International Conference on Inductive Logic Programming (ILP) 2021.
A Statistical Relational Approach to Learning Distance-based GCNs
D. S. Dhami, S. Yan, S. Natarajan. Statistical Relational AI (StarAI) Workshop at IJCLR 2021.
Bridging Graph Neural Networks and Statistical Relational Learning: Relational One-Class GCN
D. S. Dhami, S. Yan, S. Natarajan. 2021.
Explainable Models via Compression of Tree Ensembles
S. Yan, S. Natarajan, S. Joshi, R. Khardon, P. Tadepalli. IJCLR 2022 (Journal track), under review, 2022.