Arvin-xd
I am a PhD student. School is Miroelectronics of Xidian University.
Xidian UniversityNo. 2 Taibai South Road, Xi'an City, Shaanxi Province
Arvin-xd's Stars
neurosim/MLP_NeuroSim_V3.0
Benchmark framework of synaptic device technologies for a simple neural network
Stephan-kashkarov/PCNN
A Implementation of a Pulse Coupled Neural network
Confused-Pig/CreateH5File
WenxueCui/CSNet-Pytorch
Pytorch code for paper "Deep Networks for Compressed Image Sensing" and "Image Compressed Sensing Using Convolutional Neural Network"
xiaobaoonline/pytorch-in-action
kaituoxu/Conv-TasNet
A PyTorch implementation of Conv-TasNet described in "TasNet: Surpassing Ideal Time-Frequency Masking for Speech Separation" with Permutation Invariant Training (PIT).
Arvin-xd/Conv-TasNet
Conv-TasNet: Surpassing Ideal Time-Frequency Magnitude Masking for Speech Separation Pytorch's Implement
JusperLee/Conv-TasNet
Conv-TasNet: Surpassing Ideal Time-Frequency Magnitude Masking for Speech Separation Pytorch's Implement
BindsNET/bindsnet
Simulation of spiking neural networks (SNNs) using PyTorch.
Shikhargupta/Spiking-Neural-Network
Pure python implementation of SNN
JusperLee/Deep-Encoder-Decoder-Conv-TasNet
A PyTorch implementation of " AN EMPIRICAL STUDY OF CONV-TASNET "
Arvin-xd/Tutorial_Separation
This repo summarizes the tutorials, datasets, papers, codes and tools for speech separation and speaker extraction task. You are kindly invited to pull requests.
Arvin-xd/XPEsim
A simulator for RRAM-based neural processor engine.
Arvin-xd/deeplearning_ai_books
deeplearning.ai(吴恩达老师的深度学习课程笔记及资源)
Arvin-xd/PythonModelling
Scripts to model functional experimental or other phenomena, such as neuronal/device spiking, or tip-sample interactions.
wilkieolin/RRAM
Software for interfacing in-memory computation methods to physical/virtual RRAM.
fgr1986/rram_multilevel_driver
Architecture for RRAM multilevel programming
neurosim/MLP_NeuroSim_V1.0
Benchmark framework of synaptic device technologies for a simple neural network
Arvin-xd/MLP_NeuroSim_V1.0
Benchmark framework of synaptic device technologies for a simple neural network