Implementation of CSRL from the AAAI2022 paper: Constraint Sampling Reinforcement Learning: Incorporating Expertise For Faster Learning

Last update: Apr 14, 2022

Related tags

Overview

CSRL

Implementation of CSRL from the AAAI2022 paper: Constraint Sampling Reinforcement Learning: Incorporating Expertise For Faster Learning

Python: 3.6.13
Includes implementations in both tensorflow and pytorch.
See requirements.txt for required packages.

Description:
See run_experiment.ipynb to run the experiments in each domain.
The environemnts used as well as a notebook detailing how to use them are in the "environments_and_constraints" directory.
The agent implementations used are in the "agents" directory.
The "fit_environments" directory contains code for fitting the parameters of the various environments.

Todos:

Add UCRL agent and Movielens experiment code

Credits:
The rainbow implementation is based off of the rainbow tutorial: https://github.com/Curt-Park/rainbow-is-all-you-need and the segment tree class (segment_tree.py) is also their implementation. The HIV environment is from https://bitbucket.org/rlpy/rlpy/src/master/rlpy/Domains/HIVTreatment.py

Owner

GitHub Repository

Project repo for Learning Category-Specific Mesh Reconstruction from Image Collections

Learning Category-Specific Mesh Reconstruction from Image Collections Angjoo Kanazawa*, Shubham Tulsiani*, Alexei A. Efros, Jitendra Malik University

438 Dec 22, 2022

Time Delayed NN implemented in pytorch

Pytorch Time Delayed NN Time Delayed NN implemented in PyTorch. Usage kernels = [(1, 25), (2, 50), (3, 75), (4, 100), (5, 125), (6, 150)] tdnn = TDNN

79 Aug 04, 2022

Face and Body Tracking for VRM 3D models on the web.

Kalidoface 3D - Face and Full-Body tracking for Vtubing on the web! A sequal to Kalidoface which supports Live2D avatars, Kalidoface 3D is a web app t

257 Jan 02, 2023

TorchFlare is a simple, beginner-friendly, and easy-to-use PyTorch Framework train your models effortlessly.

TorchFlare TorchFlare is a simple, beginner-friendly and an easy-to-use PyTorch Framework train your models without much effort. It provides an almost

85 Dec 26, 2022

DockStream: A Docking Wrapper to Enhance De Novo Molecular Design

DockStream Description DockStream is a docking wrapper providing access to a collection of ligand embedders and docking backends. Docking execution an

72 Jan 02, 2023

Learning where to learn - Gradient sparsity in meta and continual learning

Learning where to learn - Gradient sparsity in meta and continual learning In this paper, we investigate gradient sparsity found by MAML in various co

28 Dec 09, 2022

《LightXML: Transformer with dynamic negative sampling for High-Performance Extreme Multi-label Text Classiﬁcation》(AAAI 2021) GitHub:

LightXML: Transformer with dynamic negative sampling for High-Performance Extreme Multi-label Text Classiﬁcation

76 Dec 05, 2022

Beyond imagenet attack (accepted by ICLR 2022) towards crafting adversarial examples for black-box domains.

Beyond ImageNet Attack: Towards Crafting Adversarial Examples for Black-box Domains (ICLR'2022) This is the Pytorch code for our paper Beyond ImageNet

37 Nov 23, 2022

[TPAMI 2021] iOD: Incremental Object Detection via Meta-Learning

Incremental Object Detection via Meta-Learning To appear in an upcoming issue of the IEEE Transactions on Pattern Analysis and Machine Intelligence (T

66 Jan 04, 2023

A PyTorch implementation of "From Two to One: A New Scene Text Recognizer with Visual Language Modeling Network" (ICCV2021)

From Two to One: A New Scene Text Recognizer with Visual Language Modeling Network The official code of VisionLAN (ICCV2021). VisionLAN successfully a

81 Dec 12, 2022

Code release for "Self-Tuning for Data-Efficient Deep Learning" (ICML 2021)

Self-Tuning for Data-Efficient Deep Learning This repository contains the implementation code for paper: Self-Tuning for Data-Efficient Deep Learning

101 Dec 11, 2022

An efficient and effective learning to rank algorithm by mining information across ranking candidates. This repository contains the tensorflow implementation of SERank model. The code is developed based on TF-Ranking.

SERank An efficient and effective learning to rank algorithm by mining information across ranking candidates. This repository contains the tensorflow

44 Oct 20, 2022

Weakly Supervised Segmentation with Tensorflow. Implements instance segmentation as described in Simple Does It: Weakly Supervised Instance and Semantic Segmentation, by Khoreva et al. (CVPR 2017).

Weakly Supervised Segmentation with TensorFlow This repo contains a TensorFlow implementation of weakly supervised instance segmentation as described

220 Dec 13, 2022

A complete end-to-end demonstration in which we collect training data in Unity and use that data to train a deep neural network to predict the pose of a cube. This model is then deployed in a simulated robotic pick-and-place task.

Object Pose Estimation Demo This tutorial will go through the steps necessary to perform pose estimation with a UR3 robotic arm in Unity. You’ll gain

187 Dec 24, 2022

Implementation of CSRL from the AAAI2022 paper: Constraint Sampling Reinforcement Learning: Incorporating Expertise For Faster Learning

Related tags

Overview

CSRL

Owner

Project repo for Learning Category-Specific Mesh Reconstruction from Image Collections

Time Delayed NN implemented in pytorch

Face and Body Tracking for VRM 3D models on the web.

TorchFlare is a simple, beginner-friendly, and easy-to-use PyTorch Framework train your models effortlessly.

DockStream: A Docking Wrapper to Enhance De Novo Molecular Design

Learning where to learn - Gradient sparsity in meta and continual learning

《LightXML: Transformer with dynamic negative sampling for High-Performance Extreme Multi-label Text Classiﬁcation》(AAAI 2021) GitHub:

Beyond imagenet attack (accepted by ICLR 2022) towards crafting adversarial examples for black-box domains.

[TPAMI 2021] iOD: Incremental Object Detection via Meta-Learning

A PyTorch implementation of "From Two to One: A New Scene Text Recognizer with Visual Language Modeling Network" (ICCV2021)

Code release for "Self-Tuning for Data-Efficient Deep Learning" (ICML 2021)

An efficient and effective learning to rank algorithm by mining information across ranking candidates. This repository contains the tensorflow implementation of SERank model. The code is developed based on TF-Ranking.

Weakly Supervised Segmentation with Tensorflow. Implements instance segmentation as described in Simple Does It: Weakly Supervised Instance and Semantic Segmentation, by Khoreva et al. (CVPR 2017).

A complete end-to-end demonstration in which we collect training data in Unity and use that data to train a deep neural network to predict the pose of a cube. This model is then deployed in a simulated robotic pick-and-place task.

Fast methods to work with hydro- and topography data in pure Python.

Unit-Convertor - Unit Convertor Built With Python

Motion planning environment for Sampling-based Planners

Expressive Power of Invariant and Equivaraint Graph Neural Networks (ICLR 2021)

This repository contains the accompanying code for Deep Virtual Markers for Articulated 3D Shapes, ICCV'21

A new data augmentation method for extreme lighting conditions.