Random memory adaptation model inspired by the paper: "Memory-based parameter adaptation (MbPA)"
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Updated
Mar 13, 2018 - Python
Random memory adaptation model inspired by the paper: "Memory-based parameter adaptation (MbPA)"
#WORK IN PROGRESS PyTorch Implementation of Supervised and Deep Q-Learning EWC(Elastic Weight Consolidation), introduced in "Overcoming Catastrophic Forgetting in Neural Networks"
Interpreting Bayesian inference as continual learning with a CNN
Resources collection for the hot research topic of Continual Learning, a fundamental step stone to Artificial General Intelligence (AGI).
Continual Reinforcement Learning in 3D Non-stationary Environments
Selective Forgetting of Classes and Tasks for Deep Neural Networks [In Tensorflow]
Learning in Growing Robots: Knowledge Transfer from Tadpole to Frog Robot
An automated construction of a denoising autoeconder is presented here. It features an open structure both in the generative phase and in the discriminative phase where input features can be automatically added and discarded on the fly and free of the problem- specific threshold.
This code refers to all experiments in our paper "Autonomous Deep Learning: Continual Learning Approach for Dynamic Environments"
"The Unreasonable Effectiveness of Sparse Dynamic Synapses for Continual Learning" paper project.
Code to accompany our paper "Continual learning by asymmetric loss approximation with single-side overestimation" ICCV 2019
Keras-based framework for implementing continual learning methods.
Deep Generative Replay on Permuted MNIST
Project proposal for Master's thesis on Bayesian inference in continual learning
Continual Learning methods using Episodic Memory (CLEM) in PyTorch
Repo for competition track Lifelong Robotic Vision, IROS 2019.
A pytorch compatible data loader to create sequence of tasks for Continual Learning
Lifelong Learning with Dynamically Expandable Networks, ICLR 2018
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