Implementation of Deep Deterministic Policy Gradiet Algorithm in Tensorflow

Last update: Dec 07, 2022

Overview

ddpg-aigym

Deep Deterministic Policy Gradient

Implementation of Deep Deterministic Policy Gradiet Algorithm (Lillicrap et al.arXiv:1509.02971.) in Tensorflow

How to use

git clone https://github.com/stevenpjg/ddpg-aigym.git
cd ddpg-aigym
python main.py

During training

Once trained

Learning Curve

The learning curve for InvertedPendulum-v1 environment.

Dependencies

Tensorflow (Developed in tensorflow version 0.11.0rc0 [CPU version] [GPU version])
OpenAi gym
Mujoco

Features

Batch Normalization (improvement in learning speed)
Grad-inverter (given in arXiv: arXiv:1511.04143)

Note

To use different environment

experiment= 'InvertedPendulum-v1' #specify environments here

To use batch normalization

is_batch_norm = True #batch normalization switch

Let me know if there are any issues and clarifications regarding hyperparameter tuning.

Owner

Steven Spielberg P

GitHub Repository

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Implementation of Deep Deterministic Policy Gradiet Algorithm in Tensorflow

Related tags

Overview

ddpg-aigym

Deep Deterministic Policy Gradient

How to use

During training

Once trained

Learning Curve

Dependencies

Features

Note

Owner

Steven Spielberg P

Code for Piggyback: Adapting a Single Network to Multiple Tasks by Learning to Mask Weights

Contour-guided image completion with perceptual grouping (BMVC 2021 publication)

SWA Object Detection

FaceQgen: Semi-Supervised Deep Learning for Face Image Quality Assessment

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Implementation of Deep Deterministic Policy Gradiet Algorithm in Tensorflow

Related tags

Overview

ddpg-aigym

Deep Deterministic Policy Gradient

How to use

During training

Once trained

Learning Curve

Dependencies

Features

Note

Owner

Steven Spielberg P

Code for Piggyback: Adapting a Single Network to Multiple Tasks by Learning to Mask Weights

Contour-guided image completion with perceptual grouping (BMVC 2021 publication)

SWA Object Detection

FaceQgen: Semi-Supervised Deep Learning for Face Image Quality Assessment

A-ESRGAN aims to provide better super-resolution images by using multi-scale attention U-net discriminators.

PyTorch implementation of Spiking Neural Networks trained on surrogate gradient & BPTT using snntorch.

Code for EMNLP2020 long paper: BERT-Attack: Adversarial Attack Against BERT Using BERT

THIS IS THE **OLD** PYMC PROJECT. PLEASE USE PYMC3 INSTEAD:

《Dual-Resolution Correspondence Network》(NeurIPS 2020)

Keras-retinanet - Keras implementation of RetinaNet object detection.

PyTorch Implementation of Fully Convolutional Networks. (Training code to reproduce the original result is available.)

ViSER: Video-Specific Surface Embeddings for Articulated 3D Shape Reconstruction

A computer vision pipeline to identify the "icons" in Christian paintings

This is the pytorch re-implementation of the IterNorm

Cleaned test data list of DukeMTMC-reID, ICCV2021

Real-Time-Student-Attendence-System - Real Time Student Attendence System

Simple helper library to convert a collection of numpy data to tfrecord, and build a tensorflow dataset from the tfrecord.

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Supervision Exists Everywhere: A Data Efficient Contrastive Language-Image Pre-training Paradigm

TOOD: Task-aligned One-stage Object Detection, ICCV2021 Oral

THIS IS THE OLD PYMC PROJECT. PLEASE USE PYMC3 INSTEAD: