Model-Agnostic Meta-Learning in PyTorch

Proximal Policy Optimization with Model-Agnostic Meta-Learning for Battery Energy Storage System Management in a Multi-Microgrid

Project for Deep Learning And Applied AI course at the University of "La Sapienza" in Master in Computer Science A.A. 2021/2022

Clean implementation of "Model-Agnostic Meta-Learning" in PyTorch using Facebook's Higher.

Fake News detection based on the FA-KES dataset

Model Agnostic Meta Learning in TensorFlow 2.1

Determine feasible grasp positions and orientations using a spherically transformed dataset.

MAML model finished by Tensorflow 2.2

A CNN-based MAML retains the standard principles of Model-Agnostic Meta-Learning (MAML) but integrates convolutional neural networks (CNNs) as the base architecture for feature extraction and adaptation.

An implementation of Model Agnostic Meta Learning (MAML) algorithm using pytorch

Higher-order gradients in PyTorch, Parallelized

Deep Learning Midterm Project

This is pedagogical implementation of MAML Algorithm.

A production-ready adaptive meta-learning framework for continuous self-improvement. airbornehrs (MirrorMind) is a lightweight PyTorch framework that turns standard deep learning models into self-improving systems.