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Ligra: A Lightweight Graph Processing Framework for Shared Memory
Bash Line Editor―a line editor written in pure Bash with syntax highlighting, auto suggestions, vim modes, etc. for Bash interactive sessions.
Antenna Tracker for tracking a moving model aircraft or drone with a small high-gain UHF or SHF antenna
Top-level files and pin assignment scripts for various Altera FPGAs
Parametric Contrastive Learning (ICCV2021) & GPaCo (TPAMI 2023)
Channel Optimization for Convolutional Neural Networks [ICCV2021]
Import and Export blueprint strings automagically with this handy dandy blueprint API
Open source code for AlphaFold 2.
Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.
very basic hello world app, for FHIR @Hack hackathon
completely free for everyone. Its build-in Flutter Dart.
A PyTorch implementation of SimCLR based on ICML 2020 paper "A Simple Framework for Contrastive Learning of Visual Representations"
12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
Our mission is to use cutting-edge technology to build the best timetable planner for the University of Toronto
Web interface for browsing, search and filtering recent arxiv submissions
A command line tool and library for transferring data with URL syntax, supporting DICT, FILE, FTP, FTPS, GOPHER, GOPHERS, HTTP, HTTPS, IMAP, IMAPS, LDAP, LDAPS, MQTT, POP3, POP3S, RTMP, RTMPS, RTSP…
🔗 zero-config peer-to-peer encrypted live folder syncing that respects your `.gitignore`
Source code for the 2021 CIVEMSA paper "Histopathological transfer learning for Acute Lymphoblastic Leukemia detection"
PyTorch implementation of SimCLR: A Simple Framework for Contrastive Learning of Visual Representations by T. Chen et al.
VISSL is FAIR's library of extensible, modular and scalable components for SOTA Self-Supervised Learning with images.
PyTorch implementation of SimCLR: A Simple Framework for Contrastive Learning of Visual Representations
SimCLRv2 - Big Self-Supervised Models are Strong Semi-Supervised Learners
Transferability of Histological Tissue Labels in Computational Pathology [ECCV2020]
Cross Knowledge Transfer in Computational Pathology [ICASSP2022]
Atlas of Digital Pathology for Deep Learning [CVPR2019]