28 citations · 33 across the 5 of their papers we have counts for
5 papers
Predictive variational autoencoder for learning robust representations of time-series data
Julia Huiming Wang, Dexter Tsin, Tatiana Engel
Variational autoencoders (VAEs) have been used extensively to discover low-dimensional latent factors governing neural activity and animal behavior. However, without careful model…
Topology-dependent coalescence controls scaling exponents in finite networks
Roxana Zeraati, Victor Buendía, Tatiana A. Engel +1
Multiple studies of neural avalanches across different data modalities led to the prominent hypothesis that the brain operates near a critical point. The observed exponents often i…
Spatial and temporal correlations in neural networks with structured connectivity
Yan-Liang Shi, Roxana Zeraati, Anna Levina +1
Correlated fluctuations in the activity of neural populations reflect the network's dynamics and connectivity. The temporal and spatial dimensions of neural correlations are interd…
Neural Circuit Architectural Priors for Embodied Control
Nikhil X. Bhattasali, Anthony M. Zador, Tatiana A. Engel
Artificial neural networks for motor control usually adopt generic architectures like fully connected MLPs. While general, these tabula rasa architectures rely on large amounts of…
Learning non-stationary Langevin dynamics from stochastic observations of latent trajectories
Mikhail Genkin, Owen Hughes, Tatiana A. Engel
Many complex systems operating far from the equilibrium exhibit stochastic dynamics that can be described by a Langevin equation. Inferring Langevin equations from data can reveal…