Pinned Repositories
ai4elife
This data-centric AI repository implements a robust deep learning method (LFBNet) for fully automated tumor segmentation in whole-body [18]F-FDG PET/CT images.
AutoPET-II
AutoPET2-Submission
autoPET2022_Blackbean
Grand Challenge; autoPET 2022; MICCAI 2022 challenges
Autopet_nnUNet_Train_Inf
aws_autogluon
auto_gluon
Building-a-Complete-RL-System_Demonstration
"Building a Complete RL System" demonstration code to go with RL2021 lecture
class-conditional-conformal
Data-science
Recopilatorio de materiales de la red sobre Data Science
deep_learning_tuning_playbook
A playbook for systematically maximizing the performance of deep learning models.
maxshatskiy's Repositories
maxshatskiy/ai4elife
This data-centric AI repository implements a robust deep learning method (LFBNet) for fully automated tumor segmentation in whole-body [18]F-FDG PET/CT images.
maxshatskiy/AutoPET-II
maxshatskiy/AutoPET2-Submission
maxshatskiy/autoPET2022_Blackbean
Grand Challenge; autoPET 2022; MICCAI 2022 challenges
maxshatskiy/Autopet_nnUNet_Train_Inf
maxshatskiy/aws_autogluon
auto_gluon
maxshatskiy/class-conditional-conformal
maxshatskiy/Data-science
Recopilatorio de materiales de la red sobre Data Science
maxshatskiy/deep_learning_tuning_playbook
A playbook for systematically maximizing the performance of deep learning models.
maxshatskiy/medicaldiffusion
Medical Diffusion: This repository contains the code to our paper Medical Diffusion: Denoising Diffusion Probabilistic Models for 3D Medical Image Synthesis
maxshatskiy/dinov2_medfinetuned
PyTorch code and models for the DINOv2 self-supervised learning method, own data set and own adapted training.
maxshatskiy/edm
Elucidating the Design Space of Diffusion-Based Generative Models (EDM)
maxshatskiy/elektronn3
A PyTorch-based library for working with 3D and 2D convolutional neural networks, with focus on semantic segmentation of volumetric biomedical image data
maxshatskiy/FeatUp
Official code for "FeatUp: A Model-Agnostic Frameworkfor Features at Any Resolution" ICLR 2024
maxshatskiy/hecktor_baseline
maxshatskiy/k-diffusion
Karras et al. (2022) diffusion models for PyTorch
maxshatskiy/MIM-Refiner
A Contrastive Learning Boost from Intermediate Pre-Trained Representations
maxshatskiy/MOOSE
MOOSE (Multi-organ objective segmentation) a data-centric AI solution that generates multilabel organ segmentations to facilitate systemic TB whole-person research.The pipeline is based on nn-UNet and has the capability to segment 120 unique tissue classes from a whole-body 18F-FDG PET/CT image.
maxshatskiy/MRI-preprocessing-techniques
Code examples of the free course in Youtube of brain MRI preprocessing techniques in python
maxshatskiy/notes
maxshatskiy/PANORAMA_baseline
maxshatskiy/PyTorch-VAE
A Collection of Variational Autoencoders (VAE) in PyTorch.
maxshatskiy/pytorch_lightning
maxshatskiy/SiT
Official PyTorch Implementation of "SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers"
maxshatskiy/solo-learn
solo-learn: a library of self-supervised methods for visual representation learning powered by Pytorch Lightning
maxshatskiy/SSL-sore-rule
maxshatskiy/SurgicalDINO_fork
[IPCAI'2024 (IJCARS special issue)] Surgical-DINO: Adapter Learning of Foundation Models for Depth Estimation in Endoscopic Surgery
maxshatskiy/turtle
[ICML 2024] Let Go of Your Labels with Unsupervised Transfer
maxshatskiy/uvadlc_notebooks
Repository of Jupyter notebook tutorials for teaching the Deep Learning Course at the University of Amsterdam (MSc AI), Fall 2022/Spring 2022
maxshatskiy/YOLO
An MIT rewrite of YOLOv9