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Name: andrew98

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andrew98's Projects

snn_har

Pytorch implementation of Spiking Neural Networks for Human Activity Recognition.

sports_activities_dataset

Daily sports activity dataset from UCI ML repository.

squeeze_and_excitation

PyTorch Implementation of 2D and 3D 'squeeze and excitation' blocks for Fully Convolutional Neural Networks

superfed

(SIGKDD 2022) Connected Low-Loss Subspace Learning for a Personalization in Federated Learning (https://arxiv.org/abs/2109.07628)

swin-unet

The codes for the work "Swin-Unet: Unet-like Pure Transformer for Medical Image Segmentation"

tensorflow

An Open Source Machine Learning Framework for Everyone

that

Code for AAAI paper "Two-Stream Convolution Augmented Transformer for Human Activity Recognition"

tinywase

PyTorch implementation of TinyWASE described in our paper "Compressing Speaker Extraction Model with Ultra-low Precision Quantization and Knowledge Distillation"

transformer-quantization

The final project repository for 2022 Spring COMS6998-009 Deep Learning System Performance in Columbia University.

tsfel

An intuitive library to extract features from time series

uniq

Pytorch implementation of our UniQ method, IEEE Access -- Training Multi-bit Quantized and Binarized Networks with A Learnable Symmetric Quantizer

uwb-radar-motion-recognition

Human motion recognition based on UWB radar

video-swin-transformer-pytorch

Video Swin Transformer - PyTorch

vim

Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model

vit-pytorch

Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch

wiar

WiFi-based activity recognition dataset

wifi-localization

Implement SpotFi in Python. Referring to MATLAB implementation by @egaebel

wivelo_secon22

[SECON 2022] " WiVelo: Fine-grained Walking Velocity Estimation for Wi-Fi Passive Tracking" by Chenning Li, Li Liu, Zhichao Cao, and Mi Zhang.

xethru-explorer

Hold the latest version XeThru Explorer temporally

yj4889-optimized-quantization-for-convolutional-deep-neural-networks-in-federated-learning

Federated learning is a distributed learning method that trains a deep network on user devices

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