andrewcheng2016

Pinned Repositories

andrewcheng2016.github.io
Language:CSS0 1 00
C-for-Everyone
Language:C++00
C_Learning
Record of learning C/C++
Language:C++0 1 00
Cuda
Numba
Language:Python0 1 01
full_stack_open_2022
00
GPU_GSPCA
Python and C/C++ library for fast, accurate PCA on the GPU
Language:C++00
GPU_NIPALS_GS_PCA
PYCUDA implementation of the PCA algorithm
Language:Jupyter Notebook00
IFFCNN
GPU Implementation of FFCNN
Language:Python00
Interpretable-FeedForward-CNNs
Interpretable Feedforward Convolutional Neural Networks: Implemented using Saab transform in cascade with Least Square Regressor for constructing the layers. Test on MNIST Handwritten digit dataset.
Language:Python0 0 00
Interpretable_CNNs_via_Feedforward_design
Official Implementation for FF_designed CNNs
Language:Jupyter Notebook00

andrewcheng2016's Repositories

andrewcheng2016/andrewcheng2016.github.io
Language:CSS0 1 00
andrewcheng2016/C-for-Everyone
Language:C++00
andrewcheng2016/C_Learning
Record of learning C/C++
Language:C++0 1 00
andrewcheng2016/Cuda
Numba
Language:Python0 1 01
andrewcheng2016/full_stack_open_2022
00
andrewcheng2016/GPU_GSPCA
Python and C/C++ library for fast, accurate PCA on the GPU
Language:C++00
andrewcheng2016/GPU_NIPALS_GS_PCA
PYCUDA implementation of the PCA algorithm
Language:Jupyter Notebook00
andrewcheng2016/IFFCNN
GPU Implementation of FFCNN
Language:Python00
andrewcheng2016/Interpretable-FeedForward-CNNs
Interpretable Feedforward Convolutional Neural Networks: Implemented using Saab transform in cascade with Least Square Regressor for constructing the layers. Test on MNIST Handwritten digit dataset.
Language:Python0 0 00
andrewcheng2016/Interpretable_CNNs_via_Feedforward_design
Official Implementation for FF_designed CNNs
Language:Jupyter Notebook00
andrewcheng2016/AutoClicker
An application for auto-clicking mouse.
Language:HTML
andrewcheng2016/My-Website
Language:HTML