APA APA 7th

Vance-Moreau, P. H., & Deshmukh, D. S. (2026). Quantum-Inspired Variational Autoencoders for Anomaly Detection in High-Dimensional Financial Transaction Data. Journal of Ongoing Artificial Intelligence Innovations, 1(2), 73-79.

MLA MLA 9th

Vance-Moreau, Prof. Hélène, and Dr. Sunita Deshmukh. "Quantum-Inspired Variational Autoencoders for Anomaly Detection in High-Dimensional Financial Transaction Data." Journal of Ongoing Artificial Intelligence Innovations, vol. 1, no. 2, 2026, pp. 73-79.

CHI Chicago

Vance-Moreau, Prof. Hélène, and Dr. Sunita Deshmukh. "Quantum-Inspired Variational Autoencoders for Anomaly Detection in High-Dimensional Financial Transaction Data." Journal of Ongoing Artificial Intelligence Innovations 1, no. 2 (2026): 73-79.

HAR Harvard

Vance-Moreau, P. H. & Deshmukh, D. S. (2026) 'Quantum-Inspired Variational Autoencoders for Anomaly Detection in High-Dimensional Financial Transaction Data', Journal of Ongoing Artificial Intelligence Innovations, 1(2), pp. 73-79.

IEEE IEEE

P. H. Vance-Moreau, and D. S. Deshmukh, "Quantum-Inspired Variational Autoencoders for Anomaly Detection in High-Dimensional Financial Transaction Data," Journal of Ongoing Artificial Intelligence Innovations, vol. 1, no. 2, pp. 73-79, 2026.

VAN Vancouver

Vance-Moreau PH, Deshmukh DS. Quantum-Inspired Variational Autoencoders for Anomaly Detection in High-Dimensional Financial Transaction Data. Journal of Ongoing Artificial Intelligence Innovations. 2026;1(2):73-79.

BIB BibTeX

@article{prof2026,
  title     = {Quantum-Inspired Variational Autoencoders for Anomaly Detection in High-Dimensional Financial Transaction Data},
  author    = {Prof. Hélène Vance-Moreau and Dr. Sunita Deshmukh},
  journal   = {Journal of Ongoing Artificial Intelligence Innovations},
  volume    = {1},
  number    = {2},
  pages     = {73-79},
  year      = {2026},
}

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