- J. Sleeman, J. E. Dorband, and M. Halem, "A hybrid quantum enabled RBM advantage: convolutional autoencoders for quantum image compression and generative learning", InProceedings, Quantum Information Science, Sensing, and Computation XII, May 2020, 86 downloads.
- J. Sleeman, J. E. Dorband, and M. Halem, "A Hybrid Quantum Enabled RBM Advantage: Convolutional Autoencoders for Quantum Image Compression and Generative Learning", Article, arXiv preprint arXiv:2001.11946, January 2020, 208 downloads.
- J. Sleeman, M. Halem, and J. E. Dorband, "RBM Image Generation Using the D-Wave 2000Q", Misc, D-Wave Qubits North America Conference, September 2019, 183 downloads.
- J. Sleeman, "Variational Autoencoders using D-Wave Quantum Annealing", InProceedings, American Geophysical Union Fall Meeting Abstracts, December 2018.
- Y. Gui, "Convexification and Deconvexification for Training Artificial Neural Networks", PhdThesis, May 2016, 37 downloads.
- J. Lo, Y. Gui, and Y. Peng, "The Normalized Risk-Averting Error Criterion for Avoiding Nonglobal Local Minima in Training Neural Networks", Article, Neurocomputing, February 2015, 40 downloads.
- Y. Gui, J. Lo, and Y. Peng, "A pairwise algorithm for training multilayer perceptrons with the normalized risk-averting error criterion", InProceedings, International Joint Conference on Neural Networks (IJCNN), July 2014, 46 downloads.