no code implementations • 27 Apr 2024 • Tony Gracious, Ambedkar Dukkipati
This is done using a dynamic graph representation learning framework that can capture complex relationships involving multiple entities.
no code implementations • 28 Jan 2023 • Tony Gracious, Arman Gupta, Ambedkar Dukkipati
We believe that this is the first work that solves the problem of forecasting higher-order directional interactions.
no code implementations • 19 Dec 2021 • Tony Gracious, Ambedkar Dukkipati
As far as our knowledge, this is the first work that uses the temporal point process to forecast hyperedges in dynamic networks.
no code implementations • 8 Sep 2021 • Ambedkar Dukkipati, Tony Gracious, Shubham Gupta
Lockdowns are one of the most effective measures for containing the spread of a pandemic.
no code implementations • 5 Nov 2020 • Tony Gracious, Ambedkar Dukkipati
In this paper we propose an approach that achieves both modality fusion and the capability to learn embeddings of unseen nodes.
no code implementations • 26 Nov 2019 • Tony Gracious, Shubham Gupta, Arun Kanthali, Rui M. Castro, Ambedkar Dukkipati
These techniques are different for homogeneous and heterogeneous networks because heterogeneous networks can have multiple types of edges and nodes as opposed to a homogeneous network.