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Lifelong learning is a long-standing aim for artificial agents that act in dynamic environments in which an agent needs to accumulate knowledge incrementally without forgetting previously learned representations. Contemporary methods for incremental learning from images are predominantly based on frame-based data recorded by conventional shutter ca...
Lifelong learning is a long-standing aim for artificial agents that act in dynamic environments, in which an agent needs to accumulate knowledge incrementally without forgetting previously learned representations. We investigate methods for learning from data produced by event cameras and compare techniques to mitigate forgetting while learning inc...
Abstract—Grow-when-required networks such as the Growing Dual-Memory (GDM) networks possess a dynamic network structure, expanding to accommodate new neurons in response to learning novel concepts. Over time, it may be necessary to prune obsolete neurons and/or neural connections to meet performance or resource limitations. GDM networks utilize an...
We are working on a deep learning system architecture that can extract relevant information from neuroimaging data and dynamically generate visual and descriptive explanations of varying granularity on demand. Checkout https://explaination.net for more details.