Ali Hashemi's Projects
Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes
A PyTorch implementation of the Transformer model in "Attention is All You Need".
A curated list of awesome Deep Learning tutorials, projects and communities.
All materials you need for Federated Learning: blogs, videos, papers, and softwares, etc.
Federated learning on graph and tabular data related papers, frameworks, and datasets.
Everything about federated learning, including research papers, books, codes, tutorials, videos and beyond
Curated List of Persian Natural Language Processing and Information Retrieval Tools and Resources
Preprocessing of Cam-CAN's MEG/EEG data
This is a repository for summarizing my academic and industrial accomplishments including my two-pages resume, detailed CV, and a full list of my publications.
This repo contains the code for the paper "Efficient hierarchical Bayesian inference for spatio-temporal regression models in neuroimaging" that has been accepted to NeurIPS 2021.
generates eeg data
This is a repo to collect all useful materials covering federated learning, XAI, and uncertainty estimation in machine learning and deep learning.
Federated posterior averaging implemented in JAX
In this project, we design Finite Impose Response Filter layout with SOC Encounter.
The https://www.freeCodeCamp.org open source codebase and curriculum. Learn to code for free together with millions of people.
This repository contains the codes for producing results in the following paper:
A fast, clean, responsive Hugo theme.
:octocat: (Weekly Update) Python / C++11 Solutions of All 1240 LeetCode Problems
source localisation of MEG signal
MNE : Magnetoencephalography (MEG) and Electroencephalography (EEG) in Python
The python implementation of the BSBL algorithms for block sparse signal recovery
In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.
implements common ML algorithms for time series data analysis
Temporal Pattern Attention for Multivariate Time Series Forecasting
This is the link for my main webpage