Biomemetic Learning with Stochastic Neural Networks:
- Neuromorphic Deep Learning Machines E Neftci, C Augustine, S Paul, G Detorakis arXiv preprint arXiv:1612.05596
- Stochastic synapses enable efficient brain-inspired learning machines EO Neftci, BU Pedroni, S Joshi, M Al-Shedivat, G Cauwenberghs Frontiers in Neuroscience 10
Hardware/Materials: Reversible hysteretic electronic phase transitions in correlated electron materials such as VO2 to experimentally compact neuron-oscillators. Previous work on VO2 metal-insulator transition materials are:
- E. Freeman, G. Stone, N. Shukla, H. Paik, J. A. Moyer, Z. Cai, H. Wen, R. Engel-Herbert, D. G. Schlom, V. Gopalan, and S. Datta, “Nanoscale structural evolution of electrically driven insulator to metal transition in vanadium dioxide,” Appl. Phys. Lett., vol. 103, no. 26, pp. 6–9, 2013.