Connections between Support Vector Machines, Wasserstein distance and gradient-penalty GANs
Alexia Jolicoeur-Martineau, Ioannis Mitliagkas : https://arxiv.org/abs/1910.06922
#PyTorch code: https://github.com/AlexiaJM/MaximumMarginGANs
#SupportVectorMachines #GenerativeAdversarialNetworks
Alexia Jolicoeur-Martineau, Ioannis Mitliagkas : https://arxiv.org/abs/1910.06922
#PyTorch code: https://github.com/AlexiaJM/MaximumMarginGANs
#SupportVectorMachines #GenerativeAdversarialNetworks
arXiv.org
Gradient penalty from a maximum margin perspective
A popular heuristic for improved performance in Generative adversarial networks (GANs) is to use some form of gradient penalty on the discriminator. This gradient penalty was originally motivated...
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
Code: https://github.com/shaohua0116/MMAML-Classification
Paper: https://arxiv.org/abs/1910.13616
#NeurIPS #MachineLearning #ML #code
GitHub
GitHub - shaohua0116/MMAML-Classification: An official PyTorch implementation of “Multimodal Model-Agnostic Meta-Learning via Task…
An official PyTorch implementation of “Multimodal Model-Agnostic Meta-Learning via Task-Aware Modulation” (NeurIPS 2019) by Risto Vuorio*, Shao-Hua Sun*, Hexiang Hu, and Joseph J. Lim - GitHub - sh...
PyTorch: An Imperative Style, High-Performance Deep Learning Library
Paszke et al.: https://arxiv.org/abs/1912.01703
#ArtificialIntelligence #deepLearning #PyTorch
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
CVXPY creates powerful new PyTorch and TensorFlow layers
Agrawal et al.: https://locuslab.github.io/2019-10-28-cvxpylayers/
#PyTorch #TensorFlow #NeurIPS2019
locuslab.github.io
Differentiable Convex Optimization Layers
CVXPY creates powerful new PyTorch and TensorFlow layers
"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
CVXPY creates powerful new PyTorch and TensorFlow layers
Agrawal et al.: https://locuslab.github.io/2019-10-28-cvxpylayers/
#PyTorch #TensorFlow #NeurIPS2019
locuslab.github.io
Differentiable Convex Optimization Layers
CVXPY creates powerful new PyTorch and TensorFlow layers
PyTorch: An Imperative Style, High-Performance Deep Learning Library
Paszke et al.: https://arxiv.org/abs/1912.01703
#ArtificialIntelligence #DeepLearning #PyTorch
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
http://thetartan.org/2019/11/11/scitech/brain-thoughts
http://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
The PyTorch Geometry package is a geometric computer vision library for PyTorch
By Arraiy: https://github.com/arraiy/torchgeometry
#ArtificialIntelligence #ComputerVision #DeepLearning #MachineLearning #PyTorch
GitHub
GitHub - kornia/kornia: Open Source Differentiable Computer Vision Library
Open Source Differentiable Computer Vision Library - GitHub - kornia/kornia: Open Source Differentiable Computer Vision Library
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
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
GitHub
jkoutsikakis/pytorch-wrapper
Provides a systematic and extensible way to build, train, evaluate, and tune deep learning models using PyTorch. - jkoutsikakis/pytorch-wrapper
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
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
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: http://bit.ly/EnzymePDF
More: http://bit.ly/EnzymeML
#ML #MachineLearning #PyTorch #TensorFlowJS #NeurIPS #tensorflow #AI
Paper: http://bit.ly/EnzymePDF
More: http://bit.ly/EnzymeML
#ML #MachineLearning #PyTorch #TensorFlowJS #NeurIPS #tensorflow #AI