Excited to present at #NeurIPS2019 this week!! I identify challenges in hyperparameter search when training sequential autoencoders (SAEs) on sparse data such as neural spiking, and present new methods to address them.

Wed 10:45a, East B+C #138 👨‍💼
Paper: tinyurl.com/lfads-hp-opt We use SAEs to model dynamics underlying neural population activity. With small datasets, hyperparameters (HPs) can be critical. But SAEs are prone to a type of overfitting that is challenging to detect, making it difficult to adjust HPs automatically.