Publications
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, FisherBures 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 LowRank 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. MarchandMaillet, SpaceTime Local Embeddings, NIPS 28, pp. 100–108, 2015.

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

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

J. Wang, K. Sun, F. Sha, S. MarchandMaillet, A. Kalousis, TwoStage 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.