jb33k's repositories
awd-lstm-lm-ThinkNet
Code for the paper "Think Again Networks, the Delta Loss, and an Application in Language Modeling"
market-pricing
npm Javascript package of algorithms for finding competitive equilibrium prices in microeconomics from supply/demand functions or order queues
BayesianOptimization
A Python implementation of global optimization with gaussian processes.
binance-triangle-arbitrage
Detect in-market cryptocurrency arbitrage
conversational-datasets
Datasets for conversational AI
DeepRL-Tutorials
Contains high quality implementations of Deep Reinforcement Learning algorithms written in PyTorch
dexon
Official golang DEXON fullnode implementation
dl-4-tsc
Deep Learning for Time Series Classification
gpt-2-simple
Python package to easily retrain OpenAI's GPT-2 text-generating model on new texts
hacker-news-gpt-2
Dump of generated texts from GPT-2 trained on Hacker News titles
hncynic
Generate Hacker News Comments from Titles
Megatron-LM
Ongoing research training transformer language models at scale, including: BERT
naacl-mpqa-srl4orl
SRL4ORL: Improving Opinion Role Labeling Using Multi-Task Learning With Semantic Role Labeling
PdfReg
PdfReg is a web tool, which gets text at selected regions of pdf document.
ProductTitleSummarizationCorpus
Dataset for CIKM 2018 paper "Multi-Source Pointer Network for Product Title Summarization"
pymarl
Beta code release for Python Multi-Agent Reinforcement Learning framework
pytorch-a2c-ppo-acktr-gail
PyTorch implementation of Advantage Actor Critic (A2C), Proximal Policy Optimization (PPO), Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation (ACKTR) and Generative Adversarial Imitation Learning (GAIL).
rlkit
Collection of reinforcement learning algorithms
sentiment-discovery
Unsupervised Language Modeling at scale for robust sentiment classification
smoke.js
Small but good javascript smoke effect 🌬💨
Stock-Prediction-Models
Gathers machine learning and deep learning models for Stock forecasting, included trading bots and simulations
Stock-Trading-Environment
A custom OpenAI gym environment for simulating stock trades on historical price data.
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.
STROTSS
Style Transfer by Relaxed Optimal Transport and Self-Similarity (CVPR 2019)
tests
Common tests for all Ethereum implementations
Time-Series
The purpose of this repo is to implement & analyze various deep learning and hybrid approaches to time-series classification and regression problems, as well as compare performance to more traditional statistical methods.
uae
Uncertainty Autoencoders, AISTATS 2019
wsae-lstm
implementation of WSAE-LSTM model as defined by Bao, Yue, Rao (2017)