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Command line tool for working with OpenStreetMap data based on the Osmium library.
Google's differential privacy libraries.
Playing around with Phyiscs-Informed Neural Networks
BertViz: Visualize Attention in Transformer Models
Simple Implementation of many GAN models with PyTorch.
Batch stream loop data from MnDOT JSON feed and calculate performance measures; convert XML configuration of detectors to polyline shapefile
This repo includes introduction, code and dataset of our paper Deep Sequence Learning with Auxiliary Information for Traffic Prediction (KDD 2018).
Traffic prediction is the task of predicting future traffic measurements (e.g. volume, speed, etc.) in a road network (graph), using historical data (timeseries).
PyTorch implementation of GAIL and AIRL based on PPO.
Inverse RL algorithms (APP, MaxEnt, GAIL, VAIL)
A simple implementation of Generative Adversarial Imitation Learning with PyTorch
PyTorch implementation of Advantage Actor Critic (A2C), Proximal Policy Optimization (PPO), Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation (ACKT…
Clean PyTorch implementations of imitation and reward learning algorithms
PyTorch implementations of Generative Adversarial Networks.
This repository is about modelling of flocking behaviour.
General Dial A Ride Problem (DARP) made with the pyomo package in python.
Additional topics in Computational Social Science
VIP cheatsheets for Stanford's CS 221 Artificial Intelligence
Network Science with Python and NetworkX Quick Start Guide, published by Packt
FinRL®: Financial Reinforcement Learning. 🔥
Distributed Asynchronous Hyperparameter Optimization in Python
A library for ready-made reinforcement learning agents and reusable components for neat prototyping
PyTorch implementation of Asynchronous Advantage Actor Critic (A3C) from "Asynchronous Methods for Deep Reinforcement Learning".
An Open Source Machine Learning Framework for Everyone
Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.