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Found 3 papers, 1 papers with code
Non-Vacuous Generalization Bounds for Large Language Models
Modern language models can contain billions of parameters, raising the question of whether they can generalize beyond the training data or simply regurgitate their training corpora.
Unsupervised learning on spontaneous retinal activity leads to efficient neural representation geometry
Prior to the onset of vision, neurons in the developing mammalian retina spontaneously fire in correlated activity patterns known as retinal waves.
Learning Efficient Coding of Natural Images with Maximum Manifold Capacity Representations
The resulting method is closely related to and inspired by advances in the field of self supervised learning (SSL), and we demonstrate that MMCRs are competitive with state of the art results on standard SSL benchmarks.
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