Six comments from the community and responses from the original authors

The Cycle Generative adversarial Network, or CycleGAN for short, is a generator model for converting images from one domain to another domain. For example, the model can be used to translate images of horses to images of zebras, or photographs of city landscapes…

Since Jan. 2019, I have started leading a team at Tencent AI Lab and working on a new system GNES (Generic Neural Elastic Search). GNES is an open-sou ... · Han Xiao

Let's look at compression methods for neural networks, such as quantization and pruning. Then, we apply one to BERT using TensorFlow Lite.

Training neural networks can be very confusing! What’s a good learning rate? How many hidden layers should your network have? Is dropout actually useful? Why are your gradients vanishing? In this p…

GauGAN plugin for GIMP. Contribute to prusnak/gimp-plugin-gaugan development by creating an account on GitHub.

Discussions:
Hacker News (64 points, 3 comments), Reddit r/MachineLearning (219 points, 18 comments)


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This year, we saw a dazzling application of machine learning. The OpenAI GPT…

bsuite is a collection of carefully-designed experiments that investigate core capabilities of a reinforcement learning (RL) agent - google-deepmind/bsuite

Recently, Facebook AI has advanced state-of-the-art results in key language understanding tasks and also launched a new benchmark to push AI systems further

A new paper by Liu, Jian, He et al introduces RAdam, or “Rectified Adam”. It’s a new variation of the classic Adam optimizer that provides…

Explore and run machine learning code with Kaggle Notebooks | Using data from Meta Kaggle

This post expands on the NAACL 2019 tutorial on Transfer Learning in NLP. It highlights key insights and takeaways and provides updates based on recent work.

PyTorch original implementation of Cross-lingual Language Model Pretraining. - facebookresearch/XLM

Explore and run machine learning code with Kaggle Notebooks | Using data from Understanding Clouds from Satellite Images

A data visualization curriculum of interactive notebooks. - uwdata/visualization-curriculum

Hi all,The theme of this newsletter are juxtapositions: training ever bigger models (GPT-8 8B) vs. making models smaller (via distillation or compression); powerful models (see Tools ⚒) vs. dumb models à la Clever Hans, i.e. that only appear to be able to…

By Aaron Gokaslan* and Vanya Cohen*

Что делать, если вам нужно нарисовать граф, но попавшиеся под руку инструменты рисуют какой-то комок волос или вовсе пожирают всю оперативную память и вешают систему? За последние пару лет работы с...

In this tutorial, you will learn how to train your own custom dlib shape predictor. You'll then learn how to take your trained dlib shape predictor and use it to predict landmarks on input images and real-time video streams.