wolfhu

Pinned Repositories

• A-Dual-Stage-Attention-Based-Recurrent-Neural-Network-for-Time-Series-Prediction

  Language:Python10

• ABCNN

  Implmentiaion of ABCNN(Attention-Based Convolutional Neural Network) on Tensorflow

  Language:Python00

• adda

  Language:Python00

• Arena-Baselines

  Arena: A General Evaluation Platform and Building Toolkit for Single/Multi-Agent Intelligence. AAAI 2020.

  Language:ASP10

• AttentionXML

  Implementation for "AttentionXML: Label Tree-based Attention-Aware Deep Model for High-Performance Extreme Multi-Label Text Classification"

  Language:Python1100

• CNN_sentence

  CNNs for sentence classification

  Language:Python1200

• LINE

  LINE: Large-scale information network embedding

  Language:C++10

• LSTMRelatedness

  Attempt at using LSTMs to predict semantic relatedness of sentences (a la Tai et al. in Improved Semantic Representations From Tree-Structured Long Short-Term Memory Networks, Kai Sheng Tai, Richard Socher, and Christopher D. Manning)

  Language:Python22304

• stockpredictionai

  In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.

  1100

wolfhu's Repositories