One solution approach is model-agnostic continual meta-learning, whereby both task-specific and meta parameters are trained. Here, we depart from this view and ...
One solution approach is model-agnostic continual meta-learning, whereby both task-specific and meta parameters are trained. Here, we depart from this view and ...
Jinyung Hong, Theodore P. Pavlic: Learning to modulate random weights can induce task-specific contexts for economical meta and continual learning.
Apr 8, 2022 · We introduce a novel neural network architecture inspired by neuromodulation in biological nervous systems to economically and efficiently address catastrophic ...
Missing: induce meta
Jun 4, 2024 · Learning to modulate random weights can induce task-specific contexts for economical meta and continual learning. CoRR abs/2204.04297 (2022) ...
Learning to modulate random weights can induce task-specific contexts for economical meta and continual learning · Jinyung Hong, Theodore P. Pavlic. 2022 ...
Learning to modulate random weights can induce task-specific contexts for economical meta and continual learning · Preprint · File available. April 2022. ·. 68 ...
Learning to modulate random weights can induce task-specific contexts for economical meta and continual learning · pdf icon · hmtl icon · Jinyung Hong, Theodore ...
Learning to modulate random weights can induce task-specific contexts for economical meta and continual learning. View Code Notebook Code for Similar Papers ...
Learning to modulate random weights can induce task-specific contexts for economical meta and continual learning. Neural networks are vulnerable to ...