Default mode network connectivity in stable vs progressive mild cognitive impairment JR Petrella, FC Sheldon, SE Prince, VD Calhoun, PM Doraiswamy
Neurology 76 (6), 511-517, 2011
364 2011 Predicting cognitive decline in subjects at risk for Alzheimer disease by using combined cerebrospinal fluid, MR imaging, and PET biomarkers JL Shaffer, JR Petrella, FC Sheldon, KR Choudhury, VD Calhoun, ...
Radiology 266 (2), 583-591, 2013
328 * 2013 Evidence of Exponential Speed‐Up in the Solution of Hard Optimization Problems FL Traversa, P Cicotti, F Sheldon, M Di Ventra
Complexity 2018 (1), 7982851, 2018
42 2018 Taming a nonconvex landscape with dynamical long-range order: Memcomputing ising benchmarks F Sheldon, FL Traversa, M Di Ventra
Physical Review E 100 (5), 053311, 2019
34 * 2019 The backpropagation algorithm implemented on spiking neuromorphic hardware A Renner, F Sheldon, A Zlotnik, L Tao, A Sornborger
Nature Communications 15 (1), 9691, 2024
31 2024 Global minimization via classical tunneling assisted by collective force field formation F Caravelli, FC Sheldon, FL Traversa
Science Advances 7 (52), eabh1542, 2021
24 2021 Conducting-insulating transition in adiabatic memristive networks FC Sheldon, M Di Ventra
Physical Review E 95 (1), 012305, 2017
22 2017 Stress-testing memcomputing on hard combinatorial optimization problems F Sheldon, P Cicotti, FL Traversa, M Di Ventra
IEEE transactions on neural networks and learning systems 31 (6), 2222-2226, 2019
18 2019 Computational capacity of FC Sheldon, A Kolchinsky, F Caravelli
Physical Review E 106 (4), 045310, 2022
14 2022 Critical branching processes in digital memcomputing machines SRB Bearden, F Sheldon, M Di Ventra
Europhysics Letters 127 (3), 30005, 2019
10 2019 Phases of memristive circuits via an interacting disorder approach F Caravelli, FC Sheldon
arXiv preprint arXiv:2009.00114, 2020
4 2020 Fully analog memristive circuits for optimization tasks: A comparison FC Sheldon, F Caravelli, C Coffrin
Handbook of Unconventional Computing: VOLUME 2: Implementations, 193-213, 2022
3 2022 The computational capacity of Mem-LRC reservoirs F Sheldon, F Caravelli
Proceedings of the 2020 Annual Neuro-Inspired Computational Elements …, 2020
3 2020 Number of attractors in the critical Kauffman model is exponential TMA Fink, FC Sheldon
Physical Review Letters 131 (26), 267402, 2023
2 2023 Implementing backpropagation for learning on neuromorphic spiking hardware A Renner, F Sheldon, A Zlotnik, L Tao, A Sornborger
Proceedings of the 2020 Annual Neuro-Inspired Computational Elements …, 2020
2 2020 Phase-dependent noise in Josephson junctions F Sheldon, S Peotta, M Di Ventra
The European Physical Journal Applied Physics 81 (1), 10601, 2018
2 2018 Insights from number theory into the critical Kauffman model with connectivity one F Sheldon, T Fink
Journal of Physics A: Mathematical and Theoretical, 2023
1 2023 The computational capacity of memristor reservoirs FC Sheldon, A Kolchinsky, F Caravelli
Arxiv manuscript, 2020
1 2020 Simple solution of the critical Kauffman model with connectivity one TMA Fink, FC Sheldon
networks 104, 048701, 2010
1 2010 Network analysis of memristive device circuits: dynamics, stability andcorrelations F Barrows, F Caravelli, F Sheldon
Journal of Physics: Complexity, 2025
2025 
M. Di VentraProfessor of Physics, University of California, San DiegoEmail verificata su physics.ucsd.edu
