104 citations · 125 across the 15 of their papers we have counts for
4 papers · 1 filter
Comparing Dynamical Models Through Diffeomorphic Vector Field Alignment
Ruiqi Chen, Giacomo Vedovati, Todd Braver +1
Dynamical systems models such as recurrent neural networks (RNNs) are increasingly popular in theoretical neuroscience for hypothesis-generation and data analysis. Evaluating the d…
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…
Representation Learning for Context-Dependent Decision-Making
Yuzhen Qin, Tommaso Menara, Samet Oymak +2
Humans are capable of adjusting to changing environments flexibly and quickly. Empirical evidence has revealed that representation learning plays a crucial role in endowing humans…
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…