Brian Baingana

Orcid: 0000-0002-8310-5793

According to our database1, Brian Baingana authored at least 21 papers between 2013 and 2019.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of five.

Timeline

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Bibliography

2019
Nonlinear Structural Vector Autoregressive Models With Application to Directed Brain Networks.
IEEE Trans. Signal Process., 2019

2017
Tensor Decompositions for Identifying Directed Graph Topologies and Tracking Dynamic Networks.
IEEE Trans. Signal Process., 2017

Kernel-Based Structural Equation Models for Topology Identification of Directed Networks.
IEEE Trans. Signal Process., 2017

Tracking Switched Dynamic Network Topologies From Information Cascades.
IEEE Trans. Signal Process., 2017

Topology inference of directed graphs using nonlinear structural vector autoregressive models.
Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

2016
Joint Community and Anomaly Tracking in Dynamic Networks.
IEEE Trans. Signal Process., 2016

Tracking dynamic piecewise-constant network topologies via adaptive tensor factorization.
Proceedings of the 2016 IEEE Global Conference on Signal and Information Processing, 2016

Egonet tensor decomposition for community identification.
Proceedings of the 2016 IEEE Global Conference on Signal and Information Processing, 2016

Nonlinear structural equation models for network topology inference.
Proceedings of the 2016 Annual Conference on Information Science and Systems, 2016

Inferring directed network topologies via tensor factorization.
Proceedings of the 50th Asilomar Conference on Signals, Systems and Computers, 2016

2015
Kernel-based embeddings for large graphs with centrality constraints.
Proceedings of the 2015 IEEE International Conference on Acoustics, 2015

Switched dynamic structural equation models for tracking social network topologies.
Proceedings of the 2015 IEEE Global Conference on Signal and Information Processing, 2015

Dynamic and decentralized learning of overlapping network communities.
Proceedings of the 6th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2015

Robust kriged Kalman filtering.
Proceedings of the 49th Asilomar Conference on Signals, Systems and Computers, 2015

2014
Proximal-Gradient Algorithms for Tracking Cascades Over Social Networks.
IEEE J. Sel. Top. Signal Process., 2014

A proximal gradient algorithm for tracking cascades over networks.
Proceedings of the IEEE International Conference on Acoustics, 2014

Tracking anomalous community memberships in time-varying networks.
Proceedings of the 2014 IEEE Global Conference on Signal and Information Processing, 2014

2013
Dynamic Structural Equation Models for Social Network Topology Inference.
CoRR, 2013

Centrality-constrained graph embedding.
Proceedings of the IEEE International Conference on Acoustics, 2013

Identifiability of sparse structural equation models for directed and cyclic networks.
Proceedings of the IEEE Global Conference on Signal and Information Processing, 2013

Dynamic structural equation models for tracking topologies of social networksy.
Proceedings of the 5th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2013


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