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Name: Stanford Intelligent and Interactive Autonomous Systems Group
Type: Organization
Bio: Stanford Intelligent and Interactive Autonomous Systems Group
Location: Stanford University
Name: Stanford Intelligent and Interactive Autonomous Systems Group
Type: Organization
Bio: Stanford Intelligent and Interactive Autonomous Systems Group
Location: Stanford University
Companion code for RSS 2020 paper: "Active Preference-Based Gaussian Process Regression for Reward Learning"
A Library for Active Preference-based Reward Learning Algorithms
Dictionary for accessing nested keys
Companion code to CoRL 2018 paper: E Bıyık, D Sadigh. "Batch Active Preference-Based Learning of Reward Functions". Conference on Robot Learning (CoRL), Zurich, Switzerland, Oct. 2018.
2D Driving Simulator
PyTorch implementation for "On the Critical Role of Conventions in Adaptive Human-AI Collaboration", ICLR 2021
Public code release for "Generating Language Corrections for Teaching Physical Control Tasks" (ICML 2023).
Winter 2020 CS237B Homework 1
Winter2020 CS237B Homework 2
Exploring techniques to generate diverse conventions in multi-agent settings
Companion code to the preprint: E Bıyık, K Wang, N Anari, D Sadigh, "Batch Active Learning using Determinantal Point Processes". arXiv preprint arXiv:1906.07975, Dec. 2019.
Public release for "Distillation and Retrieving Generalizable Knowledge for Robot Manipulation via Language Corrections"
Companion code to CoRL 2019 paper: E Bıyık, M Palan, NC Landolfi, DP Losey, D Sadigh. "Asking Easy Questions: A User-Friendly Approach to Active Reward Learning". 3rd Conference on Robot Learning (CoRL), Osaka, Japan, Oct. 2019.
Reward shaping approach for instruction following settings, leveraging language at multiple levels of abstraction.
Companion code for IJCAI 2021 paper "Emergent Prosociality in Multi-Agent Games Through Gifting"
Public release for "Explore until Confident: Efficient Exploration for Embodied Question Answering"
running fetch from openrave
A toolkit for developing and comparing reinforcement learning algorithms.
Companion code for ICML 2022 paper "Imitation Learning by Estimating Expertise of Demonstrators"
Code for the paper 'Learning from Imperfect Demonstrations from Agents with Varying Dynamics'
Code for 'Learning Feasibility to Imitate Demonstrators with Different Dynamics'
Code & Experiments for CoRL 2021 Paper "LILA: Language-Informed Latent Actions." Mirrored from https://github.com/siddk/lila.
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.