5 citations · 6 across the 6 of their papers we have counts for
8 papers
Ca-tunable mechanics and recoil in reconstituted Tcb2 networks
Xiangting Lei, K. R. Prathyusha, Carlos Floyd +2
Tetrahymena calcium-binding protein (Tcb2) forms Ca-responsive networks that exhibit contractile behavior, yet how Ca concentration controls their local mechanical re…
Coherent advantage in the computational expressivity of excitonic networks
Matthew Du, Carlos Floyd, Dipti Jasrasaria +1
The rising energy consumption of AI has generated interest in physical systems as alternative substrates for trainable computation. Recent experimental advances have enabled precis…
In-context learning emerges in chemical reaction networks without attention
Carlos Floyd, Hector Manuel Lopez Rios, Aaron R. Dinner +1
We investigate whether chemical processes can perform in-context learning (ICL), a mode of computation typically associated with transformer architectures. ICL allows a system to i…
Local imperfect feedback control in non-equilibrium biophysical systems enabled by thermodynamic constraints
Carlos Floyd, Aaron R. Dinner, Suriyanarayanan Vaikuntanathan
How biological networks achieve robust control despite relying on imperfect, local information remains an important open question. Here, we identify thermodynamic constraints that…
Tailoring interactions between active nematic defects with reinforcement learning
Carlos Floyd, Aaron R. Dinner, Suriyanarayanan Vaikuntanathan
Active nematics, formed from a liquid crystalline suspension of active force dipoles, are a paradigmatic active matter system whose study provides insights into how chemical drivin…
Non-equilibrium active noise enhances generative memory in diffusion models
Agnish Kumar Behera, Alexandra Lamtyugina, Aditya Nandy +3
Generative diffusion models have emerged as powerful tools for sampling high-dimensional distributions, yet they typically rely on white gaussian noise and noise schedules to destr…
Limits on the computational expressivity of non-equilibrium biophysical processes
Carlos Floyd, Aaron R. Dinner, Arvind Murugan +1
Many biological decision-making processes can be viewed as performing a classification task over a set of inputs, using various chemical and physical processes as "biological hardw…
Learning to control non-equilibrium dynamics using local imperfect gradients
Carlos Floyd, Aaron R. Dinner, Suriyanarayanan Vaikuntanathan
Standard approaches to controlling dynamical systems involve biologically implausible steps such as backpropagation of errors or intermediate model-based system representations. Re…