Topic: sequence generation

Apply neural networks to biological sequence analysis, including sequence classification, functional-feature discovery, source tracking and sequence generation. Hands-on notebooks introduce sequence encoding and language-model concepts, progressing from convolutional networks and LSTMs to attention and Transformers. Exercises use TensorFlow and Keras to connect model training and performance evaluation with the biological interpretation of genomic data. 2027-01-25–2027-01-27, 14:00–20:00 daily, Europe/Berlin (CET, UTC+01:00). Online course; fee €480. Participants should be familiar with Pytho

In the brain, the collective activity of neurons form trajectories on low dimensional neural manifolds. The neural computation underlying flexible cognition and behavior relies on dynamic control of these structures. For example, different tasks or behaviors are represented on different subspaces, requiring fast timescale subspace rotation to move from one behavior to the next. For flexibility in a particular behavior, the neural trajectory must be dynamically controllable within that behaviorally determined subspace. Here we propose mechanisms for fast timescale control of the neural subspace