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"Bayesian graph convolutional neural networks for semi-supervised classification",
Proc. AAAI Int. Conf. Artificial Intelligence, Hawaii, USA, 02/2019.
"Bayesian graph convolutional neural networks using node copying",
Proc. Learning and Reasoning with Graph-Structured Representations Workshop, (International Conference on Machine Learning), Long Beach, USA, 06/2019.
"Bayesian graph convolutional neural networks using non-parametric graph learning",
Proc. Representation Learning on Graphs and Manifolds Workshop (Int. Conf. Learning Representations), New Orleans, USA, 05/2019.
"Gaussian sum particle flow filter",
Proc. IEEE Computational Advances in Multi-Sensor Adaptive Process. (CAMSAP), Curacao, The Netherlands, IEEE, 12/2017.
Download: CAMSAP_v8.pdf (217.44 KB)
"Particle flow particle filter for Gaussian mixture noise models",
Proc. IEEE Int. Conf. Acoust., Speech and Signal Process. (ICASSP), Calgary, Canada, IEEE, 04/2018.
Download: ICASSP_v7.pdf (204.1 KB)
"Scalable MCMC in degree corrected stochastic block model",
Proc. IEEE Int. Conf. Acoust., Speech and Signal Process. (ICASSP), Brighton, UK, 05/2019.
Download: dcbm_mcmc.pdf (233.44 KB)
"Sequential MCMC with the discrete bouncy particle sampler",
Proc. IEEE Statistical Signal Processing Workshop (SSP), Freiburg, Germany, IEEE, 06/2018.
Download: ssp18_v4.pdf (210.86 KB)
"Invertible particle-flow-based sequential MCMC with extension to Gaussian mixture noise models",
IEEE Trans. Signal Processing, vol. 67, issue 9, pp. 2499-2512, 05/2019.