Neural Rank Collapse: Weight Decay and Small Within-Class Variability Yield Low-Rank Bias
Recent work in deep learning has shown strong empirical and theoretical evidence of an
implicit low-rank bias: weight matrices in deep networks tend to be approximately low-rank …
implicit low-rank bias: weight matrices in deep networks tend to be approximately low-rank …
Exploiting correlations across trials and behavioral sessions to improve neural decoding
Traditional neural decoders model the relationship between neural activity and behavior
within individual trials of a single experimental session, neglecting correlations across trials …
within individual trials of a single experimental session, neglecting correlations across trials …
Active learning of neural population dynamics using two-photon holographic optogenetics
Recent advances in techniques for monitoring and perturbing neural populations have
greatly enhanced our ability to study circuits in the brain. In particular, two-photon …
greatly enhanced our ability to study circuits in the brain. In particular, two-photon …