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Name: pikapika
Type: User
Company: the University of Tokyo
Bio: はかせ三年生 graduated
Location: Tokyo
Name: pikapika
Type: User
Company: the University of Tokyo
Bio: はかせ三年生 graduated
Location: Tokyo
Features Extraction using Autoencoders for Reinforcement Learning Tasks
[ICLR 2020] Learning Compositional Koopman Operators for Model-Based Control
Deep Reinforcement Learning
Concise pytorch implements of DRL algorithms, including REINFORCE, A2C, DQN, PPO(discrete and continuous), DDPG, TD3, SAC.
An implementation for CVRP problem with A3C+Attention mechanism and GCN
Codes to run some Dynamic Mode Decompositions (DMD) algorithms on multiple time-series data with some prebuilt choices of observables and example simulation models in python modules. The one step and N step options refer only to the predictions using the dynamics matrix rather than its estimation itself. Used research at University of California Santa Barbara (UCSB).
Computational framework for reinforcement learning in traffic control
GCN CAV
Traffic Graph Convolutional Recurrent Neural Network
Code for hierarchical imitation learning and reinforcement learning
Deep Reinforcement Learning for Keras.
Data-driven Koopman control theory applied to reinforcement learning!
Learning Continuous Image Representation with Local Implicit Image Function, in CVPR 2021 (Oral)
Task-oriented Dialog Policy Learning with Multi-Agent Reinforcement Learning
A multitask learning architecture for Natural Language Processing of Pytorch implementation
Kriging Toolkit for Python
Python Multi-Agent Reinforcement Learning framework
PyTorch implementations of various Deep Reinforcement Learning (DRL) algorithms for both single agent and multi-agent.
Combining Reinforcement Learning with Model Predictive Control for On-Ramp Merging
Model for SCALE-Net: Scalable Vehicle Trajectory Prediction Network under Random Number of Interacting Vehicles via Edge-enhanced Graph Convolutional Neural Network
Graph Neural Networks with Keras and Tensorflow 2.
StellarGraph - Machine Learning on Graphs
Spatio-Temporal Graph Convolutional Networks
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.
Temporal Graph Convolutional Network for Urban Traffic Flow Prediction Method
Codes for the study "Variational Recurrent Models for Solving Partially Observable Control Tasks", published as a conference paper at ICLR 2020 (https://openreview.net/forum?id=r1lL4a4tDB)
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.