A Lagrangian Formulation For Optical Backpropagation Training In Kerr-Type Optical Networks. - James Edward Steck; Steven R. Skinner; Alvaro A. Cruz-Cabrara; Elizabeth C. Behrman (NIPS, 1994)

A spatial quantum neural computer. - Elizabeth C. Behrman; James Edward Steck; Steven R. Skinner (IJCNN, 1999)

Optical hardware backpropagation neural network. - Steven R. Skinner; James Edward Steck; Alvaro A. Cruz-Cabrara; Mingtao Yang; Elizabeth C. Behrman (IJCNN, 1999)

Simulations of quantum neural networks. - Elizabeth C. Behrman; L. R. Nash; James Edward Steck; V. G. Chandrashekar; Steven R. Skinner (Inf. Sci., 2000)

Reinforcement and backpropagation training for an optical neural network using self-lensing effects. - Alvaro A. Cruz-Cabrara; Mingtao Yang; Guoqi Cui; Elizabeth C. Behrman; James Edward Steck; Steven R. Skinner (IEEE Trans. Neural Networks Learn. Syst., 2000)

Towards the Dynamic Learning of an Experimental Entanglement Witness. - Elizabeth C. Behrman; James Edward Steck; Preethika K. Gagnebin; Steven R. Skinner (IEEE Congress on Evolutionary Computation, 2006)

Quantum algorithm design using dynamic learning. - Elizabeth C. Behrman; James Edward Steck; Prem Kumar; K. A. Walsh (Quantum Inf. Comput., 2008)

Quantum Simulataneous Recurrent Networks for Content Addressable Memory. - Raheel Allauddin; Stuart Boehmer; Elizabeth C. Behrman; Kavitha Gaddam; James Edward Steck (Quantum Inspired Intelligent Systems, 2008)

Dynamic learning of pairwise and three-way entanglement. - Elizabeth C. Behrman; James Edward Steck (NaBIC, 2011)

A quantum neural network computes its own relative phase. - Elizabeth C. Behrman; James Edward Steck (SIS, 2013)

Multiqubit entanglement of a general input state. - Elizabeth C. Behrman; James Edward Steck (Quantum Inf. Comput., 2013)

On the Correction of Anomalous Phase Oscillation in Entanglement Witnesses Using Quantum Neural Networks. - Elizabeth C. Behrman; Richard E. F. Bonde; James Edward Steck; Joanna F. Behrman (IEEE Trans. Neural Networks Learn. Syst., 2014)

Programming quantum annealing computers using machine learning. - Elizabeth C. Behrman; James Edward Steck (SMC, 2017)

Biologically motivated quantum neural networks. - James Edward Steck; Elizabeth C. Behrman (SMC, 2017)

Learning quantum annealing. - Elizabeth C. Behrman; James Edward Steck; Mohamed A. Moustafa (Quantum Inf. Comput., 2017)

Experimental evaluation of quantum Bayesian networks on IBM QX hardware. - Sima Esfandiarpour Borujeni; Nam H. Nguyen; Saideep Nannapaneni; Elizabeth C. Behrman; James Edward Steck (QCE, 2020)

A non-algorithmic approach to "programming" quantum computers via machine learning. - Nathan L. Thompson; James Edward Steck; Elizabeth C. Behrman (QCE, 2020)

A Quantum Annealing Approach for Dynamic Multi-Depot Capacitated Vehicle Routing Problem. - Ramkumar Harikrishnakumar; Saideep Nannapaneni; Nam H. Nguyen; James Edward Steck; Elizabeth C. Behrman (CoRR, 2020)

Experimental pairwise entanglement estimation for an N-qubit system. - Nathan L. Thompson; Nam H. Nguyen; Elizabeth C. Behrman; James Edward Steck (Quantum Inf. Process., 2020)

Quantum learning with noise and decoherence: a robust quantum neural network. - Nam H. Nguyen; Elizabeth C. Behrman; James Edward Steck (Quantum Mach. Intell., 2020)

Benchmarking Neural Networks For Quantum Computations. - Nam H. Nguyen; Elizabeth C. Behrman; Mohamed A. Moustafa; James Edward Steck (IEEE Trans. Neural Networks Learn. Syst., 2020)

Quantum circuit representation of Bayesian networks. - Sima Esfandiarpour Borujeni; Saideep Nannapaneni; Nam H. Nguyen; Elizabeth C. Behrman; James Edward Steck (Expert Syst. Appl., 2021)

Qutrit-Inspired Fully Self-Supervised Shallow Quantum Learning Network for Brain Tumor Segmentation. - Debanjan Konar; Siddhartha Bhattacharyya; Bijaya K. Panigrahi; Elizabeth C. Behrman (IEEE Trans. Neural Networks Learn. Syst., 2022)