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Li, Y., S. Pal, and M. J. Coates, "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.
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Pal, S., and M. Coates, "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)
Pal, S., and M. Coates, "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)
Pal, S., and M. Coates, "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)
Pal, S., F. Regol, and M. Coates, "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.
Pal, S., and M. Coates, "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)
Pal, S., F. Regol, and M. Coates, "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.
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Zhang, Y., S. Pal, M. J. Coates, and D. Üstebay, "Bayesian graph convolutional neural networks for semi-supervised classification", Proc. AAAI Int. Conf. Artificial Intelligence, Hawaii, USA, 02/2019.