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Learning and Generalization through Neural Representations

John Murray, Yale University聽
Tuesday November 29, 12-1pm
Zoom Link:聽

础产蝉迟谤补肠迟:听Efficient generalization is essential for learning in a complex and dynamic environment. In theories of neural computation and learning, neural representations adapt to task demands, yet in turn, representations shape inductive biases for generalization during task learning. In this talk I will present neural network modeling and behavioral analysis that explores this interplay between neural representations, inductive bias, and learning behavior.聽