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Found 3 papers, 1 papers with code
On the geometry of generalization and memorization in deep neural networks
Understanding how large neural networks avoid memorizing training data is key to explaining their high generalization performance.
Generalization to Novel Objects using Prior Relational Knowledge
To solve tasks in new environments involving objects unseen during training, agents must reason over prior information about those objects and their relations.
Monaural Audio Speaker Separation with Source Contrastive Estimation
Although the matrix determined by the output weights is dependent on a set of known speakers, we only use the input vectors during inference.
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