Search Results for author:
Found 3 papers, 1 papers with code
Reproducible, incremental representation learning with Rosetta VAE
Variational autoencoders are among the most popular methods for distilling low-dimensional structure from high-dimensional data, making them increasingly valuable as tools for data exploration and scientific discovery.
Bubblewrap: Online tiling and real-time flow prediction on neural manifolds
While most classic studies of function in experimental neuroscience have focused on the coding properties of individual neurons, recent developments in recording technologies have resulted in an increasing emphasis on the dynamics of neural populations.
A Goal-Based Movement Model for Continuous Multi-Agent Tasks
Here, using the case of a two-player, real-time, continuous strategic game as an example, we show how the use of modern machine learning methods allows us to relax each of these assumptions.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
