We just released our #NeurIPS2019 Multimodal Model-Agnostic Meta-Learning (MMAML) code for learning few-shot image classification, which extends MAML to multimodal task distributions (e.g. learning from multiple datasets). The code contains #PyTorch implementations of our model and two baselines (MAML and Multi-MAML) as well as the scripts to evaluate these models to five popular few-shot learning datasets: Omniglot, Mini-ImageNet, FC100 (CIFAR100), CUB-200-2011, and FGVC-Aircraft.

Code: https://github.com/shaohua0116/MMAML-Classification

Paper: https://arxiv.org/abs/1910.13616

#NeurIPS #MachineLearning #ML #code

PyTorch: An Imperative Style, High-Performance Deep Learning Library
Paszke et al.: https://arxiv.org/abs/1912.01703
#ArtificialIntelligence #deepLearning #PyTorch

"Differentiable Convex Optimization Layers"
CVXPY creates powerful new PyTorch and TensorFlow layers
Agrawal et al.: https://locuslab.github.io/2019-10-28-cvxpylayers/
#PyTorch #TensorFlow #NeurIPS2019

"Differentiable Convex Optimization Layers"
CVXPY creates powerful new PyTorch and TensorFlow layers
Agrawal et al.: https://locuslab.github.io/2019-10-28-cvxpylayers/
#PyTorch #TensorFlow #NeurIPS2019

PyTorch: An Imperative Style, High-Performance Deep Learning Library
Paszke et al.: https://arxiv.org/abs/1912.01703
#ArtificialIntelligence #DeepLearning #PyTorch

Machine Learning Unlocks Library of The Human Brain. #BigData #Analytics #DataScience #AI #MachineLearning #IoT #IIoT #PyTorch #Python #RStats #TensorFlow #Java #JavaScript #ReactJS #GoLang #CloudComputing #Serverless #DataScientist #Linux #NeuroScience


https://thetartan.org/2019/11/11/scitech/brain-thoughts

PyTorch Geometry
The PyTorch Geometry package is a geometric computer vision library for PyTorch
By Arraiy: https://github.com/arraiy/torchgeometry
#ArtificialIntelligence #ComputerVision #DeepLearning #MachineLearning #PyTorch

PyTorch Wrapper version 1.1 is out!

New Features:

- Samplers for smart batching based on text length for faster training.

- Loss and Evaluation wrappers for token prediction tasks.

- New nn.modules for attention based models.

- Support for multi GPU training / evaluation / prediction.

- Verbose argument in system's methods.

- Examples using Transformer based models like BERT for text classification.

Check it out in the following links:

install with: pip install pytorch-wrapper

GitHub: https://github.com/jkoutsikakis/pytorch-wrapper

docs: https://pytorch-wrapper.readthedocs.io/en/latest/

examples: https://github.com/jkouts…/pytorch-wrapper/…/master/examples

#DeepLearning #PyTorch #NeuralNetworks #MachineLearning #DataScience #python #TensorFlow

PyTorch internals
https://blog.ezyang.com/2019/05/pytorch-internals/
#ArtificialIntelligence #DeepLearning #Pytorch

RLlib: Scalable Reinforcement Learning
RLlib is an open-source library for reinforcement learning that offers both high scalability and a unified API for a variety of applications.
RLlib natively supports TensorFlow, TensorFlow Eager, and PyTorch, but most of its internals are framework agnostic.
The Ray Team : https://ray.readthedocs.io/en/latest/rllib.html
#ReinforcementLearning #PyTorch #TensorFlow

MiniTorch
Sasha Rush and Ge Gao : https://minitorch.github.io/index.html
#DeepLearning #PyTorch #Python

Enzyme, a compiler plug-in for importing foreign code into systems like TensorFlow & PyTorch without having to rewrite it. v/@MIT_CSAIL

Paper: https://bit.ly/EnzymePDF

More: https://bit.ly/EnzymeML

#ML #MachineLearning #PyTorch #TensorFlowJS #NeurIPS #tensorflow #AI