AISC Blog

[Super Post] Reinforcement Learning; an Overview

This blog post is the collective work of the participants of the “RL” workshop organized by Aggregate Intellect. This post serves as a proof of work, and covers some of the concepts covered in the workshop in addition to advanced concepts pursued by the participants.

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[Super Post] Generative Adversarial Networks; an Overview

This blog post is the collective work of the participants of the “GAN” workshop organized by Aggregate Intellect. This post serves as a proof of work, and covers some of the concepts covered in the workshop in addition to advanced concepts pursued by the participants.

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Intuitively Explained: Multi-Task Learning — ERNIE 2.0 | State-of-the-Art NLP Architecture

The tech giant Baidu unveiled its state-of-the-art NLP architecture ERNIE 2.0 earlier this year, which scored

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Order Matters: Alibaba's Transformer-based Recommender System

Another step towards Alibaba’s Recommender System Domination

Alibaba, the largest e-commerce platform in

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Generating High-Resolution Images Using Deep Autoregressive Models

Going beyond GANs and capturing the diversity of the true data distribution

Generating High Fidelity Images

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Bayesian deep learning and near-term quantum computers: A cautionary tale in quantum machine learning

This blog post is an overview of quantum machine learning written by the author of the paper Bayesian deep

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Pre-training, Transformers, and Bi-directionality

Bidirectional Encoder Representations from Transformers BERT (Devlin et al., 2018) is a language

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Large-Scale Evolution of Image Classifiers

Deep neural networks excel in many difficult tasks, given large amounts of training data and enough

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Interpolation in Autoencoders via an Adversarial Regularizer

Adversarially Constrained Autoencoder Interpolation (ACAI; Berthelot et al., 2018) is a regularization

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GANs Need Some Attention, Too

Self-Attention Generative Adversarial Networks (SAGAN; Zhang et al., 2018) are convolutional neural networks

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