203 citations · 849 across the 38 of their papers we have counts for
7 papers · 1 filter
RESIDE: Improving Distantly-Supervised Neural Relation Extraction using Side Information
Shikhar Vashishth, Rishabh Joshi, Sai Suman Prayaga +2
Distantly-supervised Relation Extraction (RE) methods train an extractor by automatically aligning relation instances in a Knowledge Base (KB) with unstructured text. In addition t…
MT-CGCNN: Integrating Crystal Graph Convolutional Neural Network with Multitask Learning for Material Property Prediction
Soumya Sanyal, Janakiraman Balachandran, Naganand Yadati +4
Developing accurate, transferable and computationally inexpensive machine learning models can rapidly accelerate the discovery and development of new materials. Some of the major c…
Incorporating Syntactic and Semantic Information in Word Embeddings using Graph Convolutional Networks
Shikhar Vashishth, Manik Bhandari, Prateek Yadav +3
Word embeddings have been widely adopted across several NLP applications. Most existing word embedding methods utilize sequential context of a word to learn its embedding. While th…
HyperGCN: A New Method of Training Graph Convolutional Networks on Hypergraphs
Naganand Yadati, Madhav Nimishakavi, Prateek Yadav +3
In many real-world network datasets such as co-authorship, co-citation, email communication, etc., relationships are complex and go beyond pairwise. Hypergraphs provide a flexible…
Lovasz Convolutional Networks
Prateek Yadav, Madhav Nimishakavi, Naganand Yadati +3
Semi-supervised learning on graph structured data has received significant attention with the recent introduction of Graph Convolution Networks (GCN). While traditional methods hav…
Improving Distantly Supervised Relation Extraction using Word and Entity Based Attention
Sharmistha Jat, Siddhesh Khandelwal, Partha Talukdar
Relation extraction is the problem of classifying the relationship between two entities in a given sentence. Distant Supervision (DS) is a popular technique for developing relation…
Inductive Framework for Multi-Aspect Streaming Tensor Completion with Side Information
Madhav Nimishakavi, Bamdev Mishra, Manish Gupta +1
Low rank tensor completion is a well studied problem and has applications in various fields. However, in many real world applications the data is dynamic, i.e., new data arrives at…