Juan Pablo de la Cruz Gutiérrez's repositories

GenerativeModels

MONAI Generative Models makes it easy to train, evaluate, and deploy generative models and related applications

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MONAI

AI Toolkit for Healthcare Imaging

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monai-tutorials

MONAI Tutorials

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algorithms

Bug-tracking for Jeff's algorithms book, notes, etc.

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fastbase64

SIMD-accelerated base64 codecs

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33-js-concepts

📜 33 JavaScript concepts every developer should know.

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awesome-computational-photography

A curated list of awesome resources for topics related to computational photography via deep learning, which mainly focuses on image alignment and stitching.

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awesome-equivariant-network

Paper list for equivariant neural network

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awesome-gradient-boosting-papers

A curated list of gradient boosting research papers with implementations.

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awesome-self-supervised-learning

A curated list of awesome self-supervised methods

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base64

Fast Base64 stream encoder/decoder in C99, with SIMD acceleration

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cornucopia

An abundance of augmentation layers

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cppbestpractices

Collaborative Collection of C++ Best Practices. This online resource is part of Jason Turner's collection of C++ Best Practices resources. See README.md for more information.

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cpplinks

A categorized list of C++ resources.

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cs231n.github.io

Public facing notes page

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Delving-deep-into-GANs

A curated, quasi-exhaustive list of state-of-the-art publications and resources about Generative Adversarial Networks (GANs) and their applications.

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dijkstra3d

Dijkstra's Shortest Path for 6, 18, and 26-Connected 3D Image Volumes

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dns-weekend

Code for Implement DNS in a Weekend

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google-research

Google Research

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IsoSurface-MultiTexture

Fork of https://github.com/d3x0r/MarchingTetrahedra - adds texturing test

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kimimaro

Skeletonize densely labeled 3D image segmentations.

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mathematical-tours.github.io

Site web of the Mathematical Tours

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MICCAI-OpenSourcePapers

MICCAI 2019 Open Source Papers

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post--momentum

Why Momentum Really Works

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Self-supervised-Fewshot-Medical-Image-Segmentation

[ECCV'20] Self-supervision with Superpixels: Training Few-shot Medical Image Segmentation without Annotation (code&data-processing pipeline)

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surface-loss

Code for our MIDL 2019 talk https://openreview.net/forum?id=S1gTA5VggE

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U2PL

[CVPR 2022] Semi-Supervised Semantic Segmentation Using Unreliable Pseudo-Labels

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udlbook

Understanding Deep Learning - Simon J.D. Prince

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xor_singleheader

Header-only binary fuse and xor filter library

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zmesh

Marching Cubes & Mesh Simplification on multi-label 3D images.

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