A collection of Gradient-Based Meta-Learning Algorithms with pytorch
Python codes to implement Q-Net, a meta-learning method for few shot medical image segmentation
Optim4RL is a Jax framework of learning to optimize for reinforcement learning.
MAML and Reptile sine wave regression example in PyTorch
Modular framework for building self-modeling artificial agents with explicit internal state representation and meta-cognitive capabilities. Includes RL, hybrid, and dummy policies with integrated SelfModel monitoring and scientific metrics.
Stanford-AI-Professional-Course
A recurrent neural network surrogate model with few-shot learning strategy for CO2 storage in deep subsurface saline aquifer
Prototypical Network implementation for prototype classes that allow you to make a ranking for a concept
An implementation of Model Agnostic Meta Learning (MAML) algorithm using pytorch
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