Check out some new research from the Google AI Quantum team that sets the stage for improvements in both the construction and training of quantum #NeuralNetworks. https://t.co/yvjEmCyn97

We are open-sourcing Nevergrad, a Python3 library that makes it easier to perform gradient-free optimizations used in many machine learning tasks.

In a boon to AI researchers, the last year witnessed an unprecedented open-sourcing of large datasets by popular AI research projects.

Discussions:
Hacker News (65 points, 4 comments), Reddit r/MachineLearning (29 points, 3 comments)


Translations: Arabic, Chinese (Simplified) 1, Chinese (Simplified) 2, French 1, French 2, Italian, Japanese, Korean, Persian, Russian, Spanish 1, Spanish…

2019 edition of CMU "Neural Networks for NLP" is starting tomorrow! We'll post slides/lecture videos, feel free to follow along https://t.co/T2loGLt7be 2019 brings new classes on contextualized word representations (ELMo/BERT) and model interpretation; PyTorch/DyNet…

Hierarchical RL, external memory stores, imagination-augmented agents, and more.

From BERT’s tangled web of attention, some intuitive patterns emerge.

A new visualization tool shows how BERT forms its distinctive attention patterns.

When VAEs are trained with powerful decoders, the model can learn to 'ignore the latent variable'. This isn't something an autoencoder should do. In this post we'll take a look at why this happens ...

本文作为生日礼物题献给 @兴趣使然千里冰封，内容以深度优先遍历的方式论述。 题图为鬼人正邪。#2019-3-14 更新 在思考了各种现行翻译和词义演变的现象后，笔者最终还是决定在一些情况下将 co- 译作「余」，即将「…

强化学习特别是深度强化学习近年来取得了令人瞩目的成就，除了应用于模拟器和游戏领域，在工业领域也正取得长足的进步。

Github repo here:  https://github.com/ericjang/maml-jax Adaptive behavior in humans and animals occurs at many time scales: when I use a n...

Last year I covered some modern Variational Inference theory. These methods are often used in conjunction with Deep Neural Networks to form deep generative models (VAE, for example) or to enrich deterministic models with stochastic control, which leads to…