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Easily run experiment permutations with multi-processing and caching
A minimal web app developed with Flask
Collection of common code that's shared among different research projects in FAIR computer vision team.
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JPype is cross language bridge to allow Python programs full access to Java class libraries.
PyCIL: A Python Toolbox for Class-Incremental Learning
Hydra is a framework for elegantly configuring complex applications
Enhanced machine learning library tailored for data streams, featuring a Python API integrated with MOA backend support. This unique combination empowers users to leverage a wide array of existing…
Simple, Elegant, Typed Argument Parsing with argparse
A curated list of papers & resources linked to open set recognition, out-of-distribution, open set domain adaptation and open world recognition
Python-based research interface for blackbox and hyperparameter optimization, based on the internal Google Vizier Service.
Gradient based hyperparameter optimization & meta-learning package for TensorFlow
A Python library for advanced clustering algorithms
HAT (Hard Attention to the Task) Modules for Continual Learning
A minimal yet resourceful implementation of diffusion models (along with pretrained models + synthetic images for nine datasets)
A community-supported supercharged version of paperless: scan, index and archive all your physical documents
A continual model for human activity recognition (called HAR-GAN). It is based on a technique called `generative replay` which two models (classifier and generator) are trainined in the same time t…
A series of tutorial notebooks on denoising diffusion probabilistic models in PyTorch
Pytorch implementation of Diffusion Models (https://arxiv.org/pdf/2006.11239.pdf)
Pytorch implementation of Diffusion Models (https://arxiv.org/pdf/2006.11239.pdf)
Official source code repository for the ICML 2021 paper "Hierarchical VAEs Know What They Don't Know"
A playbook for systematically maximizing the performance of deep learning models.
A simple jeopardy style CTF website for my Working in the cloud stand