Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Priyesh Vijayan"'
Autor:
Priyesh Vijayan, Yash Chandak, Mitesh M. Khapra, Srinivasan Parthasarathy, Balaraman Ravindran
Publikováno v:
Frontiers in Big Data, Vol 5 (2022)
Many real-world applications deal with data that have an underlying graph structure associated with it. To perform downstream analysis on such data, it is crucial to capture relational information of nodes over their expanded neighborhood efficiently
Externí odkaz:
https://doaj.org/article/514668e461e14f82aedda60d02a43ac7
Autor:
Anasua Mitra, Priyesh Vijayan, Sanasam Ranbir Singh, Diganta Goswami, Srinivasan Parthasarathy, Balaraman Ravindran
Publikováno v:
2022 IEEE International Conference on Data Mining (ICDM).
Autor:
Diganta Goswami, Anasua Mitra, Ranbir Sanasam, Srinivasan Parthasarathy, Priyesh Vijayan, Balaraman Ravindran
Publikováno v:
KDD
Multiplex networks are complex graph structures in which a set of entities are connected to each other via multiple types of relations, each relation representing a distinct layer. Such graphs are used to investigate many complex biological, social,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0bd2f27df8841d01326f8092418538f3
http://arxiv.org/abs/2110.02038
http://arxiv.org/abs/2110.02038
Publikováno v:
ICASSP
Graph neural networks (GNNs) have achieved remarkable success as a framework for deep learning on graph-structured data. However, GNNs are fundamentally limited by their tree-structured inductive bias: the WL-subtree kernel formulation bounds the rep
We consider the task of generating dialogue responses from background knowledge comprising of domain specific resources. Specifically, given a conversation around a movie, the task is to generate the next response based on background knowledge about
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4f5b1c097ea747011a12528f4d6f7fd6
Towards Accurate Vehicle Behaviour Classification With Multi-Relational Graph Convolutional Networks
Autor:
Sravan Mylavarapu, Balaraman Ravindran, Mahtab Sandhu, Priyesh Vijayan, K. Madhava Krishna, Anoop M. Namboodiri
Understanding on-road vehicle behaviour from a temporal sequence of sensor data is gaining in popularity. In this paper, we propose a pipeline for understanding vehicle behaviour from a monocular image sequence or video. A monocular sequence along wi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bc65c7c27a57038f62ffbedcbe9d632a
Autor:
Sravan Mylavarapu, Balaraman Ravindran, Mahtab Sandhu, Priyesh Vijayan, K. Madhava Krishna, Anoop M. Namboodiri
Publikováno v:
IROS
We present a novel Multi-Relational Graph Convolutional Network (MRGCN) based framework to model on-road vehicle behaviors from a sequence of temporally ordered frames as grabbed by a moving monocular camera. The input to MRGCN is a multi-relational
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::36761d11716f88ac84cff99ed781722f
Publikováno v:
2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2014).