Multi-label collective classification in multi-attribute multi-relational network data. - Priyesh Vijayan; Shivashankar Subramanian; Balaraman Ravindran (ASONAM, 2014)

HOPF: Higher Order Propagation Framework for Deep Collective Classification. - Priyesh Vijayan; Yash Chandak; Mitesh M. Khapra; Balaraman Ravindran (CoRR, 2018)

Fusion Graph Convolutional Networks. - Priyesh Vijayan; Yash Chandak; Mitesh M. Khapra; Balaraman Ravindran (CoRR, 2018)

Network Representation Learning: Consolidation and Renewed Bearing. - Saket Gurukar; Priyesh Vijayan; Aakash Srinivasan; Goonmeet Bajaj; Chen Cai; Moniba Keymanesh; Saravana Kumar; Pranav Maneriker; Anasua Mitra; Vedang Patel; Balaraman Ravindran; Srinivasan Parthasarathy 001 (CoRR, 2019)

Learning policies for Social network discovery with Reinforcement learning. - Harshavardhan Kamarthi; Priyesh Vijayan; Bryan Wilder; Balaraman Ravindran; Milind Tambe (CoRR, 2019)

Influence Maximization in Unknown Social Networks: Learning Policies for Effective Graph Sampling. - Harshavardhan Kamarthi; Priyesh Vijayan; Bryan Wilder; Balaraman Ravindran; Milind Tambe (AAMAS, 2020)

Understanding Dynamic Scenes using Graph Convolution Networks. - Sravan Mylavarapu; Mahtab Sandhu; Priyesh Vijayan; K. Madhava Krishna; Balaraman Ravindran; Anoop M. Namboodiri (IROS, 2020)

Towards Accurate Vehicle Behaviour Classification With Multi-Relational Graph Convolutional Networks. - Sravan Mylavarapu; Mahtab Sandhu; Priyesh Vijayan; K. Madhava Krishna; Balaraman Ravindran; Anoop M. Namboodiri (IV, 2020)

A Unified Non-Negative Matrix Factorization Framework for Semi Supervised Learning on Graphs. - Anasua Mitra; Priyesh Vijayan; Srinivasan Parthasarathy 001; Balaraman Ravindran (SDM, 2020)

On Incorporating Structural Information to improve Dialogue Response Generation. - Nikita Moghe; Priyesh Vijayan; Balaraman Ravindran; Mitesh M. Khapra (CoRR, 2020)

Ego-GNNs: Exploiting Ego Structures in Graph Neural Networks. - Dylan Sandfelder; Priyesh Vijayan; William L. Hamilton (ICASSP, 2021)

Semi-Supervised Deep Learning for Multiplex Networks. - Anasua Mitra; Priyesh Vijayan; Sanasam Ranbir Singh; Diganta Goswami; Srinivasan Parthasarathy 001; Balaraman Ravindran (KDD, 2021)

Revisiting Link Prediction on Heterogeneous Graphs with a Multi-view Perspective. - Anasua Mitra; Priyesh Vijayan; Sanasam Ranbir Singh; Diganta Goswami; Srinivasan Parthasarathy 001; Balaraman Ravindran (ICDM, 2022)

Scaling Graph Propagation Kernels for Predictive Learning. - Priyesh Vijayan; Yash Chandak; Mitesh M. Khapra; Srinivasan Parthasarathy 001; Balaraman Ravindran (Frontiers Big Data, 2022)

Benchmarking and Analyzing Unsupervised Network Representation Learning and the Illusion of Progress. - Saket Gurukar; Priyesh Vijayan; Srinivasan Parthasarathy 001; Balaraman Ravindran; Aakash Srinivasan; Goonmeet Bajaj; Chen Cai; Moniba Keymanesh; Saravana Kumar; Pranav Maneriker; Anasua Mitra; Vedang Patel (Trans. Mach. Learn. Res., 2022)

Generative Active Learning for the Search of Small-molecule Protein Binders. - Maksym Korablyov; Cheng-Hao Liu; Moksh Jain; Almer M. van der Sloot; Eric Jolicoeur; Edward Ruediger; Andrei Cristian Nica; Emmanuel Bengio; Kostiantyn Lapchevskyi; Daniel St-Cyr; Doris Alexandra Schuetz; Victor Ion Butoi; et al. (CoRR, 2024)