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Brandon G. Jacques
Brandon G. Jacques
Verified email at virginia.edu
Title
Cited by
Cited by
Year
DeepSITH: Efficient learning via decomposition of what and when across time scales
B Jacques, Z Tiganj, M Howard, PB Sederberg
Advances in Neural Information Processing Systems 34, 27530-27541, 2021
72021
A deep convolutional neural network that is invariant to time rescaling
BG Jacques, Z Tiganj, A Sarkar, M Howard, P Sederberg
International conference on machine learning, 9729-9738, 2022
52022
Scale-invariant temporal history (sith): optimal slicing of the past in an uncertain world
TA Spears, BG Jacques, MW Howard, PB Sederberg
arXiv preprint arXiv:1712.07165, 2017
42017
SITHCon: A neural network robust to variations in input scaling on the time dimension
BG Jacques, Z Tiganj, A Sarkar, MW Howard, PB Sederberg
arXiv preprint arXiv:2107.04616 4, 2021
32021
Representing Latent Dimensions Using Compressed Number Lines
SS Maini, J Mochizuki-Freeman, CS Indi, BG Jacques, PB Sederberg, ...
2023 International Joint Conference on Neural Networks (IJCNN), 1-10, 2023
12023
Quantifying mechanisms of cognition with an experiment and modeling ecosystem
ER Weichart, KP Darby, AW Fenton, BG Jacques, RP Kirkpatrick, ...
Behavior Research Methods, 1-24, 2021
12021
Improving Brain Computer Interfaces Using Deep Scale-Invariant Temporal History Applied to Scalp Electroencephalogram Data
G Anand, A Ansari, B Dobrenz, Y Wang, BG Jacques, PB Sederberg
2021 Systems and Information Engineering Design Symposium (SIEDS), 1-6, 2021
2021
Constructing compressed number lines of latent variables using a cognitive model of memory and deep neural networks
SS Maini, J Mochizuki-Freeman, CS Indi, BG Jacques, PB Sederberg, ...
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