Search Results for author:
Found 8 papers, 6 papers with code
A Neural Network Model of Continual Learning with Cognitive Control
Here, we build on previous work and show that neural networks equipped with a mechanism for cognitive control do not exhibit catastrophic forgetting when trials are blocked.
Locally Learned Synaptic Dropout for Complete Bayesian Inference
The random failure of presynaptic vesicles to release neurotransmitters may allow the brain to sample from posterior distributions of network parameters, interpreted as epistemic uncertainty.
Statistical Learning in Speech: A Biologically Based Predictive Learning Model
Infants, adults, non-human primates and non-primates all learn patterns implicitly, and they do so across modalities.
The Structure of Systematicity in the Brain
A hallmark of human intelligence is the ability to adapt to new situations, by applying learned rules to new content (systematicity) and thereby enabling an open-ended number of inferences and actions (generativity).
Complementary Structure-Learning Neural Networks for Relational Reasoning
The neural mechanisms supporting flexible relational inferences, especially in novel situations, are a major focus of current research.
Learning Representations that Support Extrapolation
Extrapolation -- the ability to make inferences that go beyond the scope of one's experiences -- is a hallmark of human intelligence.
Compositional generalization in a deep seq2seq model by separating syntax and semantics
Standard methods in deep learning for natural language processing fail to capture the compositional structure of human language that allows for systematic generalization outside of the training distribution.
