To lift such limits, we developed an approach involving a learning algorithm, called orthogonal weights modification, with the addition of a context-dependent processing module. We demonstrated that with orthogonal weights modification to overcome catastrophic forgetting, and the context-dependent processing...
Continual learning of context-dependent processing in neural networks,程序员大本营,技术文章内容聚合第一站。
The Computational and Neural Bases of Context-Dependent Learning. Flexible behavior requires the creation, updating, and expression of memories to depend on context. While the neural underpinnings of each of these process... JB Heald,D Wolpert,M Lengyel - 《Annual Review of Neuroscience》 被引量...
Code for paperContinual Learning of Context-dependent Processing in Neural Networks. You can also get the free version fromhttps://rdcu.be/bOaa3 There is a new version based on TF2https://github.com/xuejianyong/OWM-tf2provided by Dr. Jianyong Xue, and it basically reproduces our work. Than...
2 [41] Guanxiong Zeng, Yang Chen, Bo Cui, and Shan Yu. Contin- ual learning of context-dependent processing in neural net- works. Nature Machine Intelligence, 1(8):364–372, 2019. 6, 7 3727 http-equiv="content-type"
Continual Learning of Context-dependent Processing in Neural Networks 2019 Nature Machine Intelligence Bayesian Methods [Back to top] Bayesian methods provide a principled probabilistic framework for addressing Forgetting. Paper TitleYearConference/Journal Learning to Continually Learn with the Bayesian Principle...
However, in the process of knowledge integration when learning a new task, this strategy also suffers from catastrophic forgetting due to an imbalance between old and new knowledge. To address this problem, we propose a novel replay strategy called Manifold Expansion Replay (MaER). We argue that...
catastrophic forgetting, continual learning, artificial intelligence, synaptic stabilization, context-dependent gatingHumans and most animals can learn new tasks ... NY Masse,GD Grant,DJ Freedman - 《Proceedings of the National Academy of Sciences》 被引量: 6发表: 2018年 Communication-efficient federate...
CHILD accumulates useful behaviors in reinforcement environments by using the Temporal Transition Hierarchies learning algorithm, also derived in the dissertation. This constructive algorithm generates a hierarchical, higher-order neural network that can be used for predicting context-dependent temporal sequence...
Context-dependent-Gating (XdG): ./main.py --xdg Elastic Weight Consolidation (EWC): ./main.py --ewc Synaptic Intelligence (SI): ./main.py --si Learning without Forgetting (LwF): ./main.py --lwf Functional Regularization Of the Memorable Past (FROMP): ./main.py --fromp Deep Generati...