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Feste is a free and open-source framework allowing scalable composition of NLP tasks using a graph execution model that is optimized and executed by specialized schedulers.
BARVINN: A Barrel RISC-V Neural Network Accelerator: https://barvinn.readthedocs.io/en/latest/
Lexical is an extensible text editor framework that provides excellent reliability, accessibility and performance.
Algorithms and utilities for Synthetic Aperture Radar (SAR) sensors
Over 200 figures and diagrams of the most popular deep learning architectures and layers FREE TO USE in your blog posts, slides, presentations, or papers.
Code for "Rissanen Data Analysis: Examining Dataset Characteristics via Description Length" by Ethan Perez, Douwe Kiela, and Kyungyhun Cho
Find and obliterate duplicate files, but only the ones you don't care about.
The Incredible PyTorch: a curated list of tutorials, papers, projects, communities and more relating to PyTorch.
PyTorch extensions for high performance and large scale training.
The Learning Interpretability Tool: Interactively analyze ML models to understand their behavior in an extensible and framework agnostic interface.
A high-performance Python-based I/O system for large (and small) deep learning problems, with strong support for PyTorch.
Recursive Mono & Sans is a variable font family for code & UI
A tool to detect go-arounds in Opensky data
Datasets to use the evaluation protocol for the Winograd Schema Challenge defined in the EMNLP2019 paper "How Reasonable are Common-Sense Reasoning Tasks: A Case-Study on the Winograd Schema Challe…
Repository containing code for "U-Net Fixed-Point Quantization for Medical Image Segmentation" paper at MICCAI2019
nsync is a C library that exports various synchronization primitives, such as mutexes
Microsoft SEAL is an easy-to-use and powerful homomorphic encryption library.
Cross-platform, customizable ML solutions for live and streaming media.
A user-centered Python package for differentiable probabilistic inference
keyboard layout that changes by markov frequency
Putting together some technical machine learning/artificial intelligence/math/statistics paper notes.
Code for "EigenDamage: Structured Pruning in the Kronecker-Factored Eigenbasis" https://arxiv.org/abs/1905.05934
PyTorch code for softmax variants: center loss, cosface loss, large-margin gaussian mixture, COCOLoss, ring loss
How to improve NGINX performance, security, and other important things.
PyTorch original implementation of Cross-lingual Language Model Pretraining.