Pinned Repositories
anonymous-314.github.io
customize-a-video.github.io
Rprop-Variants-Implementation-and-Performance-Comparison
The resilient back-propagation (Rprop), proposed by Riedmiller and Braun, is one of the most popular learning algorithms for neural networks in backpropagation. It overcomes the inherent disadvantages of pure gradient-descent by performing a local adaptation of the weight-updates according to the behavior of the error function.
CMSC734-FinalProject
beta-tcvae
code for "Isolating Sources of Disentanglement in Variational Autoencoders".
Facial-Expression-Recognition.Pytorch
A CNN based pytorch implementation on facial expression recognition (FER2013 and CK+), achieving 73.112% (state-of-the-art) in FER2013 and 94.64% in CK+ dataset
lord-pytorch
Pytorch re-implementation of "Demystifying Inter-Class Disentanglement", ICLR 2020.
mvcnn_pytorch
MVCNN on PyTorch
small_norb
Python wrapper to small NORB dataset
ryx19th's Repositories
ryx19th/beta-tcvae
code for "Isolating Sources of Disentanglement in Variational Autoencoders".
ryx19th/Facial-Expression-Recognition.Pytorch
A CNN based pytorch implementation on facial expression recognition (FER2013 and CK+), achieving 73.112% (state-of-the-art) in FER2013 and 94.64% in CK+ dataset
ryx19th/lord-pytorch
Pytorch re-implementation of "Demystifying Inter-Class Disentanglement", ICLR 2020.
ryx19th/mvcnn_pytorch
MVCNN on PyTorch
ryx19th/small_norb
Python wrapper to small NORB dataset