6 papers
Learnable Sequential Memory in Coupled Oscillator Networks
Taosha Guo, Fabio Pasqualetti
The Hopfield network established that static memories can be stored as energy minima of a recurrent dynamical system, yet real intelligent agents must navigate \emph{sequences} of…
Attention by Synchronization in Coupled Oscillator Networks
Fabio Pasqualetti, Taosha Guo
We address transformer attention on energy-constrained physical substrates. Softmax attention requires exponentiation and global reduction, operations with high energy cost on von…
Oscillator-Based Associative Memory with Exponential Capacity: Theory, Algorithms, and Hardware Implementation
Arie Ogranovich, Taosha Guo, Arvind R. Venkatakrishnan +3
Associative memory systems enable content-addressable storage and retrieval of patterns, a capability central to biological neural computation and artificial intelligence. Classica…
Transfer Learning for LQR Control
Taosha Guo, Fabio Pasqualetti
In this paper, we study a transfer learning framework for Linear Quadratic Regulator (LQR) control, where (i) the dynamics of the system of interest (target system) are unknown and…
Oscillatory Associative Memory with Exponential Capacity
Taosha Guo, Arie Ogranovich, Arvind R. Venkatakrishnan +3
The slowing of Moore's law and the increasing energy demands of machine learning present critical challenges for both the hardware and machine learning communities, and drive the d…
Charge-Density-Wave Oscillator Networks for Solving Combinatorial Optimization Problems
Jonas Olivier Brown, Taosha Guo, Fabio Pasqualetti +1
Many combinatorial optimization problems fall into the non-polynomial time NP-hard complexity class, characterized by computational demands that increase exponentially with the siz…