Robust Neural Machine Translation
http://ai.googleblog.com/2019/07/robust-neural-machine-translation.html
http://ai.googleblog.com/2019/07/robust-neural-machine-translation.html
Googleblog
Robust Neural Machine Translation
A 2019 Guide to Semantic Segmentation
https://heartbeat.fritz.ai/a-2019-guide-to-semantic-segmentation-ca8242f5a7fc
https://heartbeat.fritz.ai/a-2019-guide-to-semantic-segmentation-ca8242f5a7fc
Fritz ai
A 2019 Guide to Semantic Segmentation - Fritz ai
Semantic segmentation refers to the process of linking each pixel in an image to a class label. These labels could include a person, car, flower, piece of furniture, etc., just to mention a few. We can think of semantic segmentation… Continue reading A 2019…
Pix2Pix GAN Translation of Product
Sketches of Shoes to Photographs
A Gentle Introduction to Pix2Pix Generative Adversarial Network
https://machinelearningmastery.com/a-gentle-introduction-to-pix2pix-generative-adversarial-network/
Sketches of Shoes to Photographs
A Gentle Introduction to Pix2Pix Generative Adversarial Network
https://machinelearningmastery.com/a-gentle-introduction-to-pix2pix-generative-adversarial-network/
FixRes is a simple method for fixing the train-test resolution discrepancy. It can improve the performance of any convolutional neural network architecture.
Github: https://github.com/facebookresearch/FixRes
Article:https://arxiv.org/abs/1906.06423
Github: https://github.com/facebookresearch/FixRes
Article:https://arxiv.org/abs/1906.06423
GitHub
GitHub - facebookresearch/FixRes: This repository reproduces the results of the paper: "Fixing the train-test resolution discrepancy"…
This repository reproduces the results of the paper: "Fixing the train-test resolution discrepancy" https://arxiv.org/abs/1906.06423 - facebookresearch/FixRes
How to Implement Pix2Pix GAN Models From Scratch With Keras
https://machinelearningmastery.com/how-to-implement-pix2pix-gan-models-from-scratch-with-keras/
https://machinelearningmastery.com/how-to-implement-pix2pix-gan-models-from-scratch-with-keras/
MachineLearningMastery.com
How to Implement Pix2Pix GAN Models From Scratch With Keras - MachineLearningMastery.com
The Pix2Pix GAN is a generator model for performing image-to-image translation trained on paired examples. For example, the model can be used to translate images of daytime to nighttime, or from sketches of products like shoes to photographs of products.…
MNIST-GAN: Detailed step by step explanation & implementation in code
https://medium.com/@garimanishad/mnist-gan-detailed-step-by-step-explanation-implementation-in-code-ecc93b22dc60
https://medium.com/@garimanishad/mnist-gan-detailed-step-by-step-explanation-implementation-in-code-ecc93b22dc60
Medium
MNIST-GAN: Detailed step by step explanation & implementation in code
Don’t know anything about GAN? You’ve come to the right place!
Wasserstein Robust Reinforcement Learning
article:https://arxiv.org/abs/1907.13196v1
pdf: https://arxiv.org/pdf/1907.13196v1.pdf
article:https://arxiv.org/abs/1907.13196v1
pdf: https://arxiv.org/pdf/1907.13196v1.pdf
arXiv.org
Wasserstein Robust Reinforcement Learning
Reinforcement learning algorithms, though successful, tend to over-fit to training environments hampering their application to the real-world. This paper proposes $\text{W}\text{R}^{2}\text{L}$ --...
spaCy meets PyTorch-Transformers: Fine-tune BERT, XLNet and GPT-2
https://explosion.ai/blog/spacy-pytorch-transformers
https://explosion.ai/blog/spacy-pytorch-transformers
explosion.ai
spaCy meets Transformers: Fine-tune BERT, XLNet and GPT-2 · Explosion
Huge transformer models like BERT, GPT-2 and XLNet have set a new standard for accuracy on almost every NLP leaderboard. You can now use these models in spaCy, via a new interface library we've developed that connects spaCy to Hugging Face's awesome implementations.
Rapid research framework for PyTorch. The researcher's version of Keras
https://github.com/williamFalcon/pytorch-lightning
https://github.com/williamFalcon/pytorch-lightning
GitHub
GitHub - Lightning-AI/pytorch-lightning: Pretrain, finetune ANY AI model of ANY size on 1 or 10,000+ GPUs with zero code changes.
Pretrain, finetune ANY AI model of ANY size on 1 or 10,000+ GPUs with zero code changes. - Lightning-AI/pytorch-lightning
Gradient Flow Algorithms for Density Propagation in Stochastic Systems
https://arxiv.org/abs/1908.00533
https://arxiv.org/abs/1908.00533
arXiv.org
Gradient Flow Algorithms for Density Propagation in Stochastic Systems
We develop a new computational framework to solve the partial differential
equations (PDEs) governing the flow of the joint probability density functions
(PDFs) in continuous-time stochastic...
equations (PDEs) governing the flow of the joint probability density functions
(PDFs) in continuous-time stochastic...
CS231N: Convolutional Neural Networks for Visual Recognition
Stanford University course
https://www.youtube.com/playlist?list=PLzUTmXVwsnXod6WNdg57Yc3zFx_f-RYsq
Stanford University course
https://www.youtube.com/playlist?list=PLzUTmXVwsnXod6WNdg57Yc3zFx_f-RYsq
YouTube
CS231N 2017
Share your videos with friends, family, and the world
A Gentle Introduction to CycleGAN for Image Translation
https://machinelearningmastery.com/what-is-cyclegan/
https://machinelearningmastery.com/what-is-cyclegan/
TensorFlow Model Optimization Toolkit — float16 quantization halves model size
https://medium.com/tensorflow/tensorflow-model-optimization-toolkit-float16-quantization-halves-model-size-cc113c75a2fa
https://medium.com/tensorflow/tensorflow-model-optimization-toolkit-float16-quantization-halves-model-size-cc113c75a2fa
Medium
TensorFlow Model Optimization Toolkit — float16 quantization halves model size
We are very excited to add post-training float16 quantization as part of the Model Optimization Toolkit. It is a suite of tools that…
EfficientNet-EdgeTPU: Creating Accelerator-Optimized Neural Networks with AutoML
http://ai.googleblog.com/2019/08/efficientnet-edgetpu-creating.html
http://ai.googleblog.com/2019/08/efficientnet-edgetpu-creating.html
research.google
EfficientNet-EdgeTPU: Creating Accelerator-Optimized Neural Networks with AutoML
Posted by Suyog Gupta and Mingxing Tan, Software Engineers, Google Research For several decades, computer processors have doubled their performan...
GraphVite is a general graph embedding engine, dedicated to high-speed and large-scale embedding learning in various applications.
https://github.com/DeepGraphLearning/graphvite
https://github.com/DeepGraphLearning/graphvite
GitHub
GitHub - DeepGraphLearning/graphvite: GraphVite: A General and High-performance Graph Embedding System
GraphVite: A General and High-performance Graph Embedding System - GitHub - DeepGraphLearning/graphvite: GraphVite: A General and High-performance Graph Embedding System
Track human poses in real-time on Android with TensorFlow Lite
https://medium.com/tensorflow/track-human-poses-in-real-time-on-android-with-tensorflow-lite-e66d0f3e6f9e
https://medium.com/tensorflow/track-human-poses-in-real-time-on-android-with-tensorflow-lite-e66d0f3e6f9e
Medium
Track human poses in real-time on Android with TensorFlow Lite
Posted by Eileen Mao and Tanjin Prity, Engineering Practicum Interns at Google, Summer 2019
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U-GAT-IT: new model for unpaired image-to-image translation. New SOTA in unsupervised image generation
arxiv.org/abs/1907.10830
https://github.com/taki0112/UGATIT
arxiv.org/abs/1907.10830
https://github.com/taki0112/UGATIT