mbc96325

mbc96325's Stars

• GokuMohandas/Made-With-ML

  Learn how to design, develop, deploy and iterate on production-grade ML applications.

  Language:Jupyter Notebook37k1.2k715.9k

• Project-OSRM/osrm-backend

  Open Source Routing Machine - C++ backend

  Language:C++6.3k2234.6k3.3k

• openai/multiagent-particle-envs

  Code for a multi-agent particle environment used in the paper "Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments"

  Language:Python2.3k17782785

• openai/maddpg

  Code for the MADDPG algorithm from the paper "Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments"

  Language:Python1.6k15167485

• koulanurag/ma-gym

  A collection of multi agent environments based on OpenAI gym.

  Language:Python55372998

• mohammadasghari/dqn-multi-agent-rl

  Deep Q-learning (DQN) for Multi-agent Reinforcement Learning (RL)

  Language:Python3080159

• keon/policy-gradient

  Minimal Monte Carlo Policy Gradient (REINFORCE) Algorithm Implementation in Keras

  Language:Python15910543

• Mogeng/IOHMM

  Input Output Hidden Markov Model (IOHMM) in Python

  Language:Python159131835

• Finspire13/pytorch-policy-gradient-example

  A toy example of Policy Gradient implemented in Pytorch

  Language:Python902122

• hrldcpr/hungarian

  Hungarian / Munkres' algorithm for the linear assignment problem, in Python

  Language:C++7181122

• xzhou99/Dtalite_NeXTA_package

  DTALite-NEXTA Software Release

  6725339

• thangbui/streaming_sparse_gp

  Streaming sparse Gaussian process approximations

  Language:Python625631

• beyondbeneath/bezier-curved-edges-networkx

  Function to produce Bezier curves for the edges in a NetworkX graph

  Language:Python613412

• mswang12/minDQN

  A Minimal Deep Q-Network

  Language:Jupyter Notebook561332

• MIT-CAVE/rc-cli

  Language:Shell462118

• thangbui/sparseGP_powerEP

  Unifying sparse approximations for Gaussian process regression and classification, using Power EP

  Language:Python21416

• avinashu1980/Intro_Python_Gurobi

  Language:Jupyter Notebook1519

• wenjian0202/amod-abm

  Autonomous Mobility on Demand - an Agent-based Modeling Platform

  Language:Jupyter Notebook154514

• scheinerman/SimplePosets.jl

  Simple partially ordered sets for Julia

  Language:Julia9481

• mbc96325/Epidemic-spreading-model-on-public-transit

  Code for paper "Modeling Epidemic Spreading through Public Transit using Time-VaryingEncounter Network"

  Language:Python8214

• TransitGym/TransitGym.github.io

  Transit control with RL

  Language:Python8003

• mbc96325/IOHMM-for-individual-mobility-prediction

  Input-output hidden markov model for individual mobility prediction with interpretability

  Language:Python6202

• nmundru/scr

  Sparse Convex Regression

  6100

• Tskatom/IOHMM

  IOHMM Implementation

  Language:Python6202

• mbc96325/Mixture-logit-model-for-AV-adoption

  This is an archive of codes for paper "Impacts of subjective evaluations and use of existing travel modes on adoption of autonomous mobility-on-demand"

  Language:HTML3102

• scheinerman/SimplePosetAlgorithms.jl

  Additional algorithms for the SimplePoset type.

  Language:Julia335

• mbc96325/Network-performance-model

  Event-based simulation model for public transit system

  Language:Python1101