398 citations · 2.8k across the 98 of their papers we have counts for
12 papers · 1 filter
Improving Local Identifiability in Probabilistic Box Embeddings
Shib Sankar Dasgupta, Michael Boratko, Dongxu Zhang +3
Geometric embeddings have recently received attention for their natural ability to represent transitive asymmetric relations via containment. Box embeddings, where objects are repr…
Probabilistic Case-based Reasoning for Open-World Knowledge Graph Completion
Rajarshi Das, Ameya Godbole, Nicholas Monath +2
A case-based reasoning (CBR) system solves a new problem by retrieving `cases' that are similar to the given problem. If such a system can achieve high accuracy, it is appealing ow…
Scalable Hierarchical Agglomerative Clustering
Nicholas Monath, Avinava Dubey, Guru Guruganesh +9
The applicability of agglomerative clustering, for inferring both hierarchical and flat clustering, is limited by its scalability. Existing scalable hierarchical clustering methods…
Clustering-based Inference for Biomedical Entity Linking
Rico Angell, Nicholas Monath, Sunil Mohan +2
Due to large number of entities in biomedical knowledge bases, only a small fraction of entities have corresponding labelled training data. This necessitates entity linking models…
Unsupervised Pre-training for Biomedical Question Answering
Vaishnavi Kommaraju, Karthick Gunasekaran, Kun Li +4
We explore the suitability of unsupervised representation learning methods on biomedical text -- BioBERT, SciBERT, and BioSentVec -- for biomedical question answering. To further i…
Energy-Based Reranking: Improving Neural Machine Translation Using Energy-Based Models
Sumanta Bhattacharyya, Amirmohammad Rooshenas, Subhajit Naskar +3
The discrepancy between maximum likelihood estimation (MLE) and task measures such as BLEU score has been studied before for autoregressive neural machine translation (NMT) and res…