Guillaume Lajoie, Ph.D.
Affiliations: | 2013 | Applied Mathematics | University of Washington, Seattle, Seattle, WA |
Area:
computational neuroscienceGoogle:
"Guillaume Lajoie"Mean distance: 19.07 (cluster 17)
Parents
Sign in to add mentor| Eric Shea-Brown | grad student | 2013 | University of Washington | |
| (On driven neural assemblies: synchrony, chaos and entropy.) | ||||
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Publications
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| Williams E, Ryoo AH, Jiralerspong T, et al. (2024) Expressivity of Neural Networks with Random Weights and Learned Biases. Arxiv |
| Suárez LE, Mihalik A, Milisav F, et al. (2024) Connectome-based reservoir computing with the conn2res toolbox. Nature Communications. 15: 656 |
| Azabou M, Arora V, Ganesh V, et al. (2023) A Unified, Scalable Framework for Neural Population Decoding. Arxiv |
| Liu YH, Baratin A, Cornford J, et al. (2023) How connectivity structure shapes rich and lazy learning in neural circuits. Arxiv |
| Abrevaya G, Dumas G, Aravkin AY, et al. (2021) Learning Brain Dynamics With Coupled Low-Dimensional Nonlinear Oscillators and Deep Recurrent Networks. Neural Computation. 33: 2087-2127 |
| Recanatesi S, Farrell M, Lajoie G, et al. (2021) Predictive learning as a network mechanism for extracting low-dimensional latent space representations. Nature Communications. 12: 1417 |
| Laferriere S, Bonizzato M, Cote SL, et al. (2020) Hierarchical Bayesian optimization of spatiotemporal neurostimulations for targeted motor outputs. Ieee Transactions On Neural Systems and Rehabilitation Engineering : a Publication of the Ieee Engineering in Medicine and Biology Society |
| Lajoie G, Krouchev NI, Kalaska JF, et al. (2017) Correlation-based model of artificially induced plasticity in motor cortex by a bidirectional brain-computer interface. Plos Computational Biology. 13: e1005343 |
| Lajoie G, Lin KK, Thivierge JP, et al. (2016) Encoding in Balanced Networks: Revisiting Spike Patterns and Chaos in Stimulus-Driven Systems. Plos Computational Biology. 12: e1005258 |
| Vincent-Lamarre P, Lajoie G, Thivierge JP. (2016) Driving reservoir models with oscillations: a solution to the extreme structural sensitivity of chaotic networks. Journal of Computational Neuroscience |