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 …
Active design of two-photon holographic stimulation for identifying neural population dynamics
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 …