Home › Entities › doctoral_thesis › Brain- and Quantum Inspired Mathematical and Computational Models of Spiking Neural Networks for Deep Learning of Spatio-Temporal Data

Brain- and Quantum Inspired Mathematical and Computational Models of Spiking Neural Networks for Deep Learning of Spatio-Temporal Data

2021 doctoral thesis by Helena Bahrami at Auckland University of Technology
Place doctoral_thesis Q112359054
Press Enter · cited answer in seconds

Brain- and Quantum Inspired Mathematical and Computational Models of Spiking Neural Networks for Deep Learning of Spatio-Temporal Data

Summary

Brain- and Quantum Inspired Mathematical and Computational Models of Spiking Neural Networks for Deep Learning of Spatio-Temporal Data is a doctoral thesis[1].

Key Facts

  • Brain- and Quantum Inspired Mathematical and Computational Models of Spiking Neural Networks for Deep Learning of Spatio-Temporal Data authored Helena Bahrami[2].
  • Brain- and Quantum Inspired Mathematical and Computational Models of Spiking Neural Networks for Deep Learning of Spatio-Temporal Data's instance of is recorded as doctoral thesis[3].
  • Brain- and Quantum Inspired Mathematical and Computational Models of Spiking Neural Networks for Deep Learning of Spatio-Temporal Data's publisher is recorded as Tuwhera Open Access Publisher[4].
  • Brain- and Quantum Inspired Mathematical and Computational Models of Spiking Neural Networks for Deep Learning of Spatio-Temporal Data's language of work or name is recorded as English[5].
  • Brain- and Quantum Inspired Mathematical and Computational Models of Spiking Neural Networks for Deep Learning of Spatio-Temporal Data's country of origin is recorded as New Zealand[6].
  • Brain- and Quantum Inspired Mathematical and Computational Models of Spiking Neural Networks for Deep Learning of Spatio-Temporal Data's publication date is recorded as +2021-00-00T00:00:00Z[7].
  • Brain- and Quantum Inspired Mathematical and Computational Models of Spiking Neural Networks for Deep Learning of Spatio-Temporal Data's main subject is recorded as optimization[8].
  • Brain- and Quantum Inspired Mathematical and Computational Models of Spiking Neural Networks for Deep Learning of Spatio-Temporal Data's main subject is recorded as electroencephalography[9].
  • Brain- and Quantum Inspired Mathematical and Computational Models of Spiking Neural Networks for Deep Learning of Spatio-Temporal Data's main subject is recorded as neurodegeneration[10].
  • Brain- and Quantum Inspired Mathematical and Computational Models of Spiking Neural Networks for Deep Learning of Spatio-Temporal Data's main subject is recorded as neurotransmitter[11].
  • Brain- and Quantum Inspired Mathematical and Computational Models of Spiking Neural Networks for Deep Learning of Spatio-Temporal Data's main subject is recorded as semi-supervised learning[12].
  • Brain- and Quantum Inspired Mathematical and Computational Models of Spiking Neural Networks for Deep Learning of Spatio-Temporal Data's main subject is recorded as backpropagation[13].
  • Brain- and Quantum Inspired Mathematical and Computational Models of Spiking Neural Networks for Deep Learning of Spatio-Temporal Data's Handle ID is recorded as 10292/14694[14].
  • Brain- and Quantum Inspired Mathematical and Computational Models of Spiking Neural Networks for Deep Learning of Spatio-Temporal Data's title is recorded as Brain- and Quantum Inspired Mathematical and Computational Models of Spiking Neural Networks for Deep Learning of Spatio-Temporal Data[15].
  • Brain- and Quantum Inspired Mathematical and Computational Models of Spiking Neural Networks for Deep Learning of Spatio-Temporal Data's copyright holder is recorded as Helena Bahrami[16].
  • Brain- and Quantum Inspired Mathematical and Computational Models of Spiking Neural Networks for Deep Learning of Spatio-Temporal Data's thesis submitted to is recorded as Auckland University of Technology[17].
  • Brain- and Quantum Inspired Mathematical and Computational Models of Spiking Neural Networks for Deep Learning of Spatio-Temporal Data's on focus list of Wikimedia project is recorded as NZThesisProject[18].
  • Brain- and Quantum Inspired Mathematical and Computational Models of Spiking Neural Networks for Deep Learning of Spatio-Temporal Data's copyright status is recorded as copyrighted[19].
  • Brain- and Quantum Inspired Mathematical and Computational Models of Spiking Neural Networks for Deep Learning of Spatio-Temporal Data's thesis committee member is recorded as Nikola Kasabov[20].
  • Brain- and Quantum Inspired Mathematical and Computational Models of Spiking Neural Networks for Deep Learning of Spatio-Temporal Data's thesis committee member is recorded as Marley Vellasco[21].

Body

Designation and Status

Brain- and Quantum Inspired Mathematical and Computational Models of Spiking Neural Networks for Deep Learning of Spatio-Temporal Data's instance of is recorded as doctoral thesis[3].

References

Programmatic citations — every numbered marker resolves to a verifiable graph row below.

Direct Wikidata claims

  1. [3] ↑ . wikidata.org.
  2. [2] ↑ . wikidata.org.
  3. [4] ↑ . wikidata.org.
  4. [5] ↑ . wikidata.org.
  5. [6] ↑ . wikidata.org.
  6. [7] ↑ . wikidata.org.
  7. [8] ↑ . hdl.handle.net. hdl.handle.net. Provenance: wikidata.org.
  8. [9] ↑ . hdl.handle.net. hdl.handle.net. Provenance: wikidata.org.
  9. [10] ↑ . hdl.handle.net. hdl.handle.net. Provenance: wikidata.org.
  10. [11] ↑ . hdl.handle.net. hdl.handle.net. Provenance: wikidata.org.
  11. [12] ↑ . hdl.handle.net. hdl.handle.net. Provenance: wikidata.org.
  12. [13] ↑ . hdl.handle.net. hdl.handle.net. Provenance: wikidata.org.
  13. [14] ↑ . wikidata.org.
  14. [15] ↑ . wikidata.org.
  15. [16] ↑ . wikidata.org.
  16. [17] ↑ . wikidata.org.
  17. [18] ↑ . wikidata.org.
  18. [19] ↑ . wikidata.org.
  19. [20] ↑ . wikidata.org.
  20. [21] ↑ . wikidata.org.

Class ancestry

  1. [1] ↑ . Wikidata. wikidata.org.

📑 Cite this page

Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.

APA 4ort.xyz Knowledge Graph. (2026). Brain- and Quantum Inspired Mathematical and Computational Models of Spiking Neural Networks for Deep Learning of Spatio-Temporal Data. Retrieved May 3, 2026, from https://4ort.xyz/entity/brain-and-quantum-inspired-mathematical-and-computational-models-of-spiking-neural-networks-for-deep-learning-of-spatio-temporal-data
MLA “Brain- and Quantum Inspired Mathematical and Computational Models of Spiking Neural Networks for Deep Learning of Spatio-Temporal Data.” 4ort.xyz Knowledge Graph, 4ort.xyz, 3 May. 2026, https://4ort.xyz/entity/brain-and-quantum-inspired-mathematical-and-computational-models-of-spiking-neural-networks-for-deep-learning-of-spatio-temporal-data.
BibTeX @misc{4ortxyz_brain-and-quantum-inspired-mathematical-and-computational-models-of-spiking-neural-networks-for-deep-learning-of-spatio-temporal-data_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Brain- and Quantum Inspired Mathematical and Computational Models of Spiking Neural Networks for Deep Learning of Spatio-Temporal Data}}, year = {2026}, url = {https://4ort.xyz/entity/brain-and-quantum-inspired-mathematical-and-computational-models-of-spiking-neural-networks-for-deep-learning-of-spatio-temporal-data}, note = {Accessed: 2026-05-03}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Brain- and Quantum Inspired Mathematical and Computational Models of Spiking Neural Networks for Deep Learning of Spatio-Temporal Data — https://4ort.xyz/entity/brain-and-quantum-inspired-mathematical-and-computational-models-of-spiking-neural-networks-for-deep-learning-of-spatio-temporal-data (retrieved 2026-05-03)

Canonical URL: https://4ort.xyz/entity/brain-and-quantum-inspired-mathematical-and-computational-models-of-spiking-neural-networks-for-deep-learning-of-spatio-temporal-data · Last refreshed: