Biological neural networks adapt and learn in diverse behavioral contexts. Artificial neural
networks (ANNs) have exploited biological properties to solve complex problems. However …

Neurons of the brain never produce the same output twice even when the same stimuli are
presented; this is because of their internal noisy biological processes. Likewise, in this work …

How established behaviors are retained and stably produced by a nervous system in
constant flux remains a mystery. One possible solution is to fix the activity patterns of single …

Motivated by rapid advances in neuroengineering, we recently proposed an interventional
way of reverse engineering neural circuits that is oriented towards treating disorders. The …

Computational feasibility is a widespread concern that guides the framing and modeling of
natural and artificial intelligence. The specification of cognitive system capacities is often …

To navigate the world in an efficient manner, the brain seamlessly integrates signals
received across multiple sensory modalities. Behavioral studies have suggested that …

We study activation noise in a generative energy-based modeling setting during training for
the purpose of regularization. We prove that activation noise is a general form of dropout …