dtyulman

NMHS

AugRNN

Numpy implementation of an RNN with continuous dynamics, with additional functions to augment the network with additional neurons or modules, freeze weights, optional regularization

dtyulman.github.io

hebbff

Meta-learning local synaptic plasticity for continual familiarity detection

MAML-Pytorch

Elegant PyTorch implementation of paper Model-Agnostic Meta-Learning (MAML)

ModNN

Modular (feedforward) neural network. Cluster the inputs to the network, then train each module in the network on each cluster

nilearn

Machine learning for NeuroImaging in Python

perflash

Kuramoto model and simulations of "periodic flashing" coordinated reset stimulation

preproc

fMRI preprocessing pipeline

tddcs

Time-domain diffuse correlation spectroscopy (MIT M.Eng. thesis code)

dtyulman/hebbff

Meta-learning local synaptic plasticity for continual familiarity detection

dtyulman/tddcs

Time-domain diffuse correlation spectroscopy (MIT M.Eng. thesis code)

dtyulman/AugRNN

Numpy implementation of an RNN with continuous dynamics, with additional functions to augment the network with additional neurons or modules, freeze weights, optional regularization

dtyulman/dtyulman.github.io

dtyulman/MAML-Pytorch

Elegant PyTorch implementation of paper Model-Agnostic Meta-Learning (MAML)

dtyulman/ModNN

Modular (feedforward) neural network. Cluster the inputs to the network, then train each module in the network on each cluster

dtyulman/nilearn

Machine learning for NeuroImaging in Python

dtyulman/perflash

Kuramoto model and simulations of "periodic flashing" coordinated reset stimulation

dtyulman/preproc

fMRI preprocessing pipeline

dtyulman/torchDFINE

dtyulman/UQ-RL

Uncertainty for exploration in RL