Below is a manually maintained list of selected publications. Check my ResearchGate or DBLP for a more complete list of publications. (I have a common name and have been traveling across institutions. Sometimes people and especially machines mistake me for someone else, or vice versa.)

  • [arxiv] Ke Sun and Frank Nielsen, Lightlike Neuromanifolds, Occam’s Razor and Deep Learning, 2019 (work in progress).

  • [arxiv][codes] Ke Sun, Peter Koniusz and Zhen Wang, Fisher-Bures Adversary Graph Convolutional Networks, UAI, 2019 (to appear).

  • [arxiv] Frank Nielsen and Ke Sun. On the Chain Rule Optimal Transport Distance, 2018 (work in progress).

  • [arxiv][web] F. Nielsen and K. Sun, Clustering in Hilbert simplex geometry, 2017.

  • [link] F. Nielsen and K. Sun, Clustering in Hilbert’s Projective Geometry: The Case Studies of the Probability Simplex and the Elliptope of Correlation Matrices, Geometric Structures of Information, Springer International Publishing, 2018.

  • [arxiv] K. Sun, Intrinsic Universal Measurments of Nonlinear Embeddings, 2018. (work in progress)

  • [link] U. Akujuobi, K. Sun and X. Zhang. Mining top-$k$ Popular Datasets via a Deep Generative Model, IEEE BigData, 2018.

  • [link][codes] M. Avalos, R. Nock, C. S. Ong, J. Rouar and K. Sun, Representation Learning of Compositional Data, NeurIPS 31, pp. 6679–6689, 2018.

  • [link][arXiv] F. Nielsen and K. Sun. Guaranteed Deterministic Bounds on the Total Variation Distance between Univariate Mixtures, MLSP, Aalborg, Denmark, 2018.

  • [arxiv] F. Nielsen and K. Sun, $q$-Neurons: Neuron Activations based on Stochastic Jackson’s Derivative Operators, 2018 (work in progress).

  • K. Sun, F. Malliaros, F. Nielsen, M. Vazirgiannis, Reconstructing Uncertain Graphs Based on Low-Rank Factorizations, Entropy 2018. (poster, work in progress)

  • K. Sun and F. Nielsen, Relative Fisher Information and Natural Gradient for Learning Large Modular Models, ICML, PMLR 70, pp. 3289–3298, 2017.

  • F. Nielsen and K. Sun, Guaranteed Bounds on the Kullback–Leibler Divergence of Univariate Mixtures, IEEE Signal Processing Letters 23(1), pp. 1543–1546, 2016.

  • K. Sun, J. Wang, A. Kalousis, S. Marchand-Maillet, Space-Time Local Embeddings, NIPS 28, pp. 100–108, 2015.

  • K. Sun, J. Wang, A. Kalousis, S. Marchand-Maillet, Information Geometry and Minimum Description Length Networks, ICML, PMLR 37, pp. 49–58, 2015.

  • K. Sun and S. Marchand-Maillet, An Information Geometry of Statistical Manifold Learning, ICML, PMLR 32(2), pp. 1–9, 2014.

  • J. Wang, K. Sun, F. Sha, S. Marchand-Maillet, A. Kalousis, Two-Stage Metric Learning, ICML, PMLR 32(2), pp. 370–378, 2014.

  • K. Sun and F. Bai, Mining Weighted Association Rules without Preassigned Weights, TKDE 20(4), pp. 489–495, 2008.