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Yuhan Helena Liu
Yuhan Helena Liu
PhD Student, University of Washington
在 uw.edu 的电子邮件经过验证 - 首页
标题
引用次数
引用次数
年份
Cell-type–specific neuromodulation guides synaptic credit assignment in a spiking neural network
YH Liu, S Smith, S Mihalas, E Shea-Brown, U Sümbül
Proceedings of the National Academy of Sciences 118 (51), e2111821118, 2021
30*2021
Information-theoretic privacy in smart metering systems using cascaded rechargeable batteries
YH Liu, SH Lee, A Khisti
IEEE Signal Processing Letters 24 (3), 314-318, 2017
182017
Excitation and Inhibition Balance Underlying Epileptiform Activity.
Y Liu, V Grigorovsky, BL Bardakjian
IEEE transactions on bio-medical engineering, 2020
132020
Biologically-plausible backpropagation through arbitrary timespans via local neuromodulators
YH Liu, S Smith, S Mihalas, E Shea-Brown, U Sümbül
Advances in Neural Information Processing Systems, 2022
112022
Classification of Scalp EEG States Prior to Clinical Seizure Onset
D Jacobs, YH Liu, T Hilton, M Del Campo, PL Carlen, BL Bardakjian
IEEE journal of translational engineering in health and medicine 7, 1-3, 2019
102019
How connectivity structure shapes rich and lazy learning in neural circuits
YH Liu, A Baratin, J Cornford, S Mihalas, E Shea-Brown, G Lajoie
arXiv preprint arXiv:2310.08513, 2023
72023
Beyond accuracy: generalization properties of bio-plausible temporal credit assignment rules
YH Liu, A Ghosh, BA Richards, E Shea-Brown, G Lajoie
Advances in Neural Information Processing Systems, 2022
72022
How gradient estimator variance and bias impact learning in neural networks
A Ghosh, YH Liu, G Lajoie, K Kording, BA Richards
International Conference on Learning Representations, 2023
52023
On privacy in smart metering systems with periodically time-varying input distribution
Y Liu, A Khisti, A Mahajan
2017 IEEE Global Conference on Signal and Information Processing (GlobalSIP …, 2017
42017
Evolutionary algorithms as an alternative to backpropagation for supervised training of Biophysical Neural Networks and Neural ODEs
J Hazelden, YH Liu, E Shlizerman, E Shea-Brown
arXiv preprint arXiv:2311.10869, 2023
22023
Transition to chaos separates learning regimes and relates to measure of consciousness in recurrent neural networks
D Mastrovito, YH Liu, L Kusmierz, E Shea-Brown, C Koch, S Mihalas
bioRxiv, 2024.05. 15.594236, 2024
2024
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