Pinned Repositories
emergent
This is the new version of the emergent neural network simulation software, written now in Go (golang)
envs
Environments for simulations -- provides various examples that can be adapted
GPc
Gaussian process code in C++ including some implementations of GP-LVM and IVM.
hebbian_pretraining
Course project with Jay McClelland on Hebbian pre-training for error-driven learning. Includes attempts at reproducing the works of some authors, such as Lillicrap, T. P. et al. Random synaptic feedback weights support error backpropagation for deep learning. Nat. Commun. 7, 13276 doi: 10.1038/ncomms13276 (2016). Also includes a simple neural network framework for personal experimentation.
InfoBiGANs
Implementation of a combination of the BiGAN and InfoGAN architectures.
lapack
LAPACK development repository
motor_cognition
Learning Dynamical Models of Motor Cognition - Kalman Filters and RNNs - Project completed for CS221 at Stanford by Libby Zhang and Riley DeHaan.
ProjSpring2017
scikit-learn
scikit-learn: machine learning in Python
scot
Set Cover Optimal Teaching for Sequential Decision Making with Inverse Reinforcement Learning
Riley16's Repositories
Riley16/scot
Set Cover Optimal Teaching for Sequential Decision Making with Inverse Reinforcement Learning
Riley16/hebbian_pretraining
Course project with Jay McClelland on Hebbian pre-training for error-driven learning. Includes attempts at reproducing the works of some authors, such as Lillicrap, T. P. et al. Random synaptic feedback weights support error backpropagation for deep learning. Nat. Commun. 7, 13276 doi: 10.1038/ncomms13276 (2016). Also includes a simple neural network framework for personal experimentation.
Riley16/InfoBiGANs
Implementation of a combination of the BiGAN and InfoGAN architectures.
Riley16/motor_cognition
Learning Dynamical Models of Motor Cognition - Kalman Filters and RNNs - Project completed for CS221 at Stanford by Libby Zhang and Riley DeHaan.
Riley16/emergent
This is the new version of the emergent neural network simulation software, written now in Go (golang)
Riley16/envs
Environments for simulations -- provides various examples that can be adapted
Riley16/GPc
Gaussian process code in C++ including some implementations of GP-LVM and IVM.
Riley16/lapack
LAPACK development repository
Riley16/ProjSpring2017
Riley16/scikit-learn
scikit-learn: machine learning in Python
Riley16/vis1d
One-dimensional visual environment for modeling complex visual phenomena without slow rendering times.