5 citations · 5 across the 5 of their papers we have counts for
5 papers
DFORM: Diffeomorphic vector field alignment for assessing dynamics across learned models
Ruiqi Chen, Giacomo Vedovati, Todd Braver +1
Dynamical system models such as Recurrent Neural Networks (RNNs) have become increasingly popular as hypothesis-generating tools in scientific research. Evaluating the dynamics in…
Astrocytes as a mechanism for meta-plasticity and contextually-guided network function
Lulu Gong, Fabio Pasqualetti, Thomas Papouin +1
Astrocytes are a ubiquitous and enigmatic type of non-neuronal cell and are found in the brain of all vertebrates. While traditionally viewed as being supportive of neurons, it is…
Non-Stationary Representation Learning in Sequential Linear Bandits
Yuzhen Qin, Tommaso Menara, Samet Oymak +2
In this paper, we study representation learning for multi-task decision-making in non-stationary environments. We consider the framework of sequential linear bandits, where the age…
Input Novelty as a Control Metric for Time Varying Linear Systems
Gautam Kumar, Delsin Menolascino, ShiNung Ching
This paper introduces a framework for quantitative characterization of the controllability of time-varying linear systems (or networks) in terms of input novelty. The motivation fo…
Controlling Linear Networks with Minimally Novel Inputs
Gautam Kumar, Delsin Menolascino, MohammadMehdi Kafashan +1
In this paper, we propose a novelty-based metric for quantitative characterization of the controllability of complex networks. This inherently bounded metric describes the average…