Pinned Repositories
adder-DSE
Dataset of "Cross-layer Optimization for High Speed Adders: A Pareto Driven Machine Learning Approach"
Automatic_Speech_Recognition
End-to-end automatic speech recognition from scratch in Tensorflow
DeepLearnToolbox
Matlab/Octave toolbox for deep learning. Includes Deep Belief Nets, Stacked Autoencoders, Convolutional Neural Nets, Convolutional Autoencoders and vanilla Neural Nets. Each method has examples to get you started.
eda-forum
GAN
Resources and Implementations of Generative Adversarial Nets: GAN, DCGAN, WGAN, CGAN, InfoGAN
GradientDescentExample
Example demonstrating how gradient descent may be used to solve a linear regression problem
MICSim_V1.0
Official code of paper "MICSim: A Modular Simulator for Mixed-signal Compute-in-Memory based AI Accelerator", ASP-DAC 2025
OpenILT
An Open-source Platform for Inverse Lithography Technology Research
OpenMPL
An open multiple patterning framework
perforated-cnn-matconvnet
yuzhe630's Repositories
yuzhe630/adder-DSE
Dataset of "Cross-layer Optimization for High Speed Adders: A Pareto Driven Machine Learning Approach"
yuzhe630/eda-forum
yuzhe630/GAN
Resources and Implementations of Generative Adversarial Nets: GAN, DCGAN, WGAN, CGAN, InfoGAN
yuzhe630/Automatic_Speech_Recognition
End-to-end automatic speech recognition from scratch in Tensorflow
yuzhe630/DeepLearnToolbox
Matlab/Octave toolbox for deep learning. Includes Deep Belief Nets, Stacked Autoencoders, Convolutional Neural Nets, Convolutional Autoencoders and vanilla Neural Nets. Each method has examples to get you started.
yuzhe630/GradientDescentExample
Example demonstrating how gradient descent may be used to solve a linear regression problem
yuzhe630/MICSim_V1.0
Official code of paper "MICSim: A Modular Simulator for Mixed-signal Compute-in-Memory based AI Accelerator", ASP-DAC 2025
yuzhe630/OpenILT
An Open-source Platform for Inverse Lithography Technology Research
yuzhe630/OpenMPL
An open multiple patterning framework
yuzhe630/perforated-cnn-matconvnet
yuzhe630/splitshow
A tool for the dual-head presentation of PDF slides on Mac OS X, most likely using a laptop and a projector. The project arose out of the need to correctly project slides created with LaTeX's beamer class.
yuzhe630/transferlearning-tutorial
《迁移学习简明手册》LaTex源码