minajamshidi

minajamshidi's Stars

• ctrltz/meegsim

  Building blocks (waveforms, SNR, connectivity) for M/EEG simulations with MNE-Python

  Language:Python2

• Project-MONAI/MONAI

  AI Toolkit for Healthcare Imaging

  Language:Python5.8k1.1k

• Project-MONAI/tutorials

  MONAI Tutorials

  Language:Jupyter Notebook1.8k679

• xmindflow/Awesome-Foundation-Models-in-Medical-Imaging

  A curated list of foundation models for vision and language tasks in medical imaging

  20114

• yzhao062/WSAD

  A Collection of Resources for Weakly-supervised Anomaly Detection (WSAD)

  Language:Python15711

• state-spaces/mamba

  Mamba SSM architecture

  Language:Python13.1k1.1k

• FarnoushRJ/MambaLRP

  [NeurIPS 2024] Official implementation of the paper "MambaLRP: Explaining Selective State Space Sequence Models".

  Language:Python203

• alinlab/CSI

  CSI: Novelty Detection via Contrastive Learning on Distributionally Shifted Instances (NeurIPS 2020)

  Language:Python27562

• lukasruff/Deep-SVDD-PyTorch

  A PyTorch implementation of the Deep SVDD anomaly detection method

  Language:Python706198

• MathOnco/valis

  Virtual Alignment of pathoLogy Image Series

  Language:Python12129

• DataTalksClub/data-engineering-zoomcamp

  Free Data Engineering course!

  Language:Jupyter Notebook25k5.4k

• CamDavidsonPilon/lifelines

  Survival analysis in Python

  Language:Python2.4k560

• robi56/Survival-Analysis-using-Deep-Learning

  This repository contains morden baysian statistics and deep learning based research articles , software for survival analysis

  21368

• peng-lab/HistoBistro

  Weakly-supervised learning pipeline for histopathology images. Publications: Biomarker prediction in colorectal cancer (CRC)

  Language:Jupyter Notebook6413

• harmonic-minimization/harmoni_manuscript_codes

  Harmoni: a Method for Eliminating Spurious Interactions due to the Harmonic Components in Neuronal Data. https://doi.org/10.1016/j.neuroimage.2022.119053

  Language:Python7

• xuyk/Rosalind

  Solutions to Rosalind Bioinformatics Problems

  Language:Python114

• Shivi91/Rosalind-1

  Solutions to Rosalind Bioinformatics Problems

  Language:Python64122

• alirezadir/Machine-Learning-Interviews

  This repo is meant to serve as a guide for Machine Learning/AI technical interviews.

  Language:Jupyter Notebook4.7k830

• minajamshidi/NID

  This repository includes the MATLAB codes of Nonlinear Interaction Decomposition (NID). https://doi.org/10.1016/j.neuroimage.2020.116599

  Language:MATLAB84

• harmonic-minimization/harmoni

  A pypi package for Harmoni. citation: https://doi.org/10.1016/j.neuroimage.2022.119053

  Language:Python101

• lucidrains/vit-pytorch

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

  Language:Python20.4k3k

• garydoranjr/misvm

  Multiple-Instance Support Vector Machines

  Language:Python23981

• helblazer811/ManimML

  ManimML is a project focused on providing animations and visualizations of common machine learning concepts with the Manim Community Library.

  Language:Python2.4k143

• sandeshkatakam/NormVAE-Neuroimaging

  Code Implementation of VAE Model inspired from NormVAE Paper using PyTorch Framework on Custom dataset

  Language:Python4

• eeg-to-fmri/eeg-to-fmri

  Language:Python42

• zylon-ai/private-gpt

  Interact with your documents using the power of GPT, 100% privately, no data leaks

  Language:Python54.1k7.3k

• hila-chefer/Transformer-Explainability

  [CVPR 2021] Official PyTorch implementation for Transformer Interpretability Beyond Attention Visualization, a novel method to visualize classifications by Transformer based networks.

  Language:Jupyter Notebook1.8k241

• researchmm/MM-Diffusion

  [CVPR'23] MM-Diffusion: Learning Multi-Modal Diffusion Models for Joint Audio and Video Generation

  Language:Python39322

• iffsid/mmvae

  Multimodal Mixture-of-Experts VAE

  Language:Python19142

• mhw32/multimodal-vae-public

  A PyTorch implementation of "Multimodal Generative Models for Scalable Weakly-Supervised Learning" (https://arxiv.org/abs/1802.05335)

  Language:Python15436