Implementation of algorithms for continuous control (DDPG and NAF).

Last update: Dec 31, 2022

Overview

DEPRECATION

This repository is deprecated and is no longer maintaned. Please see a more recent implementation of RL for continuous control at jax-sac.

Description

Reimplementation of Continuous Deep Q-Learning with Model-based Acceleration and Continuous control with deep reinforcement learning.

Contributions are welcome. If you know how to make it more stable, don't hesitate to send a pull request.

Run

Use the default hyperparameters.

For NAF:

python main.py --algo NAF --env-name HalfCheetah-v2

For DDPG

python main.py --algo DDPG --env-name HalfCheetah-v2

Owner

Ilya Kostrikov

Post doc

GitHub Repository

Official PyTorch implementation of MX-Font (Multiple Heads are Better than One: Few-shot Font Generation with Multiple Localized Experts)

Introduction Pytorch implementation of Multiple Heads are Better than One: Few-shot Font Generation with Multiple Localized Expert. | paper Song Park1

97 Dec 23, 2022

nnDetection is a self-configuring framework for 3D (volumetric) medical object detection which can be applied to new data sets without manual intervention. It includes guides for 12 data sets that were used to develop and evaluate the performance of the proposed method.

What is nnDetection? Simultaneous localisation and categorization of objects in medical images, also referred to as medical object detection, is of hi

365 Jan 09, 2023

Using Clinical Drug Representations for Improving Mortality and Length of Stay Predictions

Using Clinical Drug Representations for Improving Mortality and Length of Stay Predictions Usage Clone the code to local. https://github.com/tanlab/MI

3 Oct 18, 2022

SeqAttack: a framework for adversarial attacks on token classification models

A framework for adversarial attacks against token classification models

23 Nov 25, 2022

Constructing interpretable quadratic accuracy predictors to serve as an objective function for an IQCQP problem that represents NAS under latency constraints and solve it with efficient algorithms.

IQNAS: Interpretable Integer Quadratic programming Neural Architecture Search Realistic use of neural networks often requires adhering to multiple con

0 Oct 24, 2021

Moon-patrol - A faithful recreation of the 1983 hit classic Moon Patrol for the Atari 2600 created using the Pygame library for Python

Moon Patrol A recreation of the hit Atari 2600 game, Moon Patrol Moon Patrol is

3 Apr 20, 2022

The implementation of "Shuffle Transformer: Rethinking Spatial Shuffle for Vision Transformer"

Shuffle Transformer The implementation of "Shuffle Transformer: Rethinking Spatial Shuffle for Vision Transformer" Introduction Very recently, window-

87 Nov 29, 2022

SubOmiEmbed: Self-supervised Representation Learning of Multi-omics Data for Cancer Type Classification

3 Nov 15, 2022

A series of Python scripts to access measurements from Fluke 28X meters. Fluke IR Remote Interface required.

Fluke289_data_access A series of Python scripts to access measurements from Fluke 28X meters. Fluke IR Remote Interface required. Created from informa

3 Dec 08, 2022

A Closer Look at Reference Learning for Fourier Phase Retrieval

A Closer Look at Reference Learning for Fourier Phase Retrieval This repository contains code for our NeurIPS 2021 Workshop on Deep Learning and Inver

1 Oct 28, 2021

GARCH and Multivariate LSTM forecasting models for Bitcoin realized volatility with potential applications in crypto options trading, hedging, portfolio management, and risk management

Bitcoin Realized Volatility Forecasting with GARCH and Multivariate LSTM Author: Chi Bui This Repository Repository Directory ├── README.md

113 Dec 29, 2022

Implementation of "RaScaNet: Learning Tiny Models by Raster-Scanning Image" from CVPR 2021.

RaScaNet: Learning Tiny Models by Raster-Scanning Images Deploying deep convolutional neural networks on ultra-low power systems is challenging, becau

5 Dec 26, 2022

In this project we use both Resnet and Self-attention layer for cat, dog and flower classification.

cdf_att_classification classes = {0: 'cat', 1: 'dog', 2: 'flower'} In this project we use both Resnet and Self-attention layer for cdf-Classification.

3 Nov 23, 2022

Official code base for the poster "On the use of Cortical Magnification and Saccades as Biological Proxies for Data Augmentation" published in NeurIPS 2021 Workshop (SVRHM)

Self-Supervised Learning (SimCLR) with Biological Plausible Image Augmentations Official code base for the poster "On the use of Cortical Magnificatio

8 Aug 17, 2022