most citedPykg2vec: A Python Library for Knowledge Graph Embedding

10 citations · 10 across the 1 of their papers we have counts for

collaborators

7 papers

cs.SI2019

Graph Representation Ensemble Learning

Palash Goyal, Di Huang, Sujit Rokka Chhetri +3

Representation learning on graphs has been gaining attention due to its wide applicability in predicting missing links, and classifying and recommending nodes. Most embedding metho…

cs.RO2019

String Diagrams for Assembly Planning

Jade Master, Evan Patterson, Shahin Yousfi +1

Assembly planning is a difficult problem for companies. Many disciplines such as design, planning, scheduling, and manufacturing execution need to be carefully engineered and coord…

cs.SE2019

ArduCode: Predictive Framework for Automation Engineering

Arquimedes Canedo, Palash Goyal, Di Huang +2

Automation engineering is the task of integrating, via software, various sensors, actuators, and controls for automating a real-world process. Today, automation engineering is supp…

cs.SI2019

Benchmarks for Graph Embedding Evaluation

Palash Goyal, Di Huang, Ankita Goswami +3

Graph embedding is the task of representing nodes of a graph in a low-dimensional space and its applications for graph tasks have gained significant traction in academia and indust…

cs.SI2019

Tracking Temporal Evolution of Graphs using Non-Timestamped Data

Sujit Rokka Chhetri, Palash Goyal, Arquimedes Canedo

Datasets to study the temporal evolution of graphs are scarce. To encourage the research of novel dynamic graph learning algorithms we introduce YoutubeGraph-Dyn (available at http…

cs.AI201910 cited

Pykg2vec: A Python Library for Knowledge Graph Embedding

Shih Yuan Yu, Sujit Rokka Chhetri, Arquimedes Canedo +2

Pykg2vec is an open-source Python library for learning the representations of the entities and relations in knowledge graphs. Pykg2vec's flexible and modular software architecture…