activity
20122019
most citedSuperdiffusive transport by multivalent molecular walkers moving under load

31 citations · 99 across the 13 of their papers we have counts for

collaborators

14 papers

physics.bio-ph2019★ 6 cited

Tethered single-legged molecular spiders on independent 1D tracks

David Arredondo, Darko Stefanovic

We study the motion of random walkers with residence time bias between first and subsequent visits to a site, as a model for synthetic molecular walkers composed of coupled DNAzyme…

cs.NE2016★ 10 cited

Memory and Information Processing in Recurrent Neural Networks

Alireza Goudarzi, Sarah Marzen, Peter Banda +3

Recurrent neural networks (RNN) are simple dynamical systems whose computational power has been attributed to their short-term memory. Short-term memory of RNNs has been previously…

cs.ET2015

Computational Capacity and Energy Consumption of Complex Resistive Switch Networks

Jens Burger, Alireza Goudarzi, Darko Stefanovic +1

Resistive switches are a class of emerging nanoelectronics devices that exhibit a wide variety of switching characteristics closely resembling behaviors of biological synapses. Ass…

cs.ET2015★ 1 cited

Hierarchical Composition of Memristive Networks for Real-Time Computing

Jens Bürger, Alireza Goudarzi, Darko Stefanovic +1

Advances in materials science have led to physical instantiations of self-assembled networks of memristive devices and demonstrations of their computational capability through rese…

cs.NE2015★ 1 cited

Exploring Transfer Function Nonlinearity in Echo State Networks

Alireza Goudarzi, Alireza Shabani, Darko Stefanovic

Supralinear and sublinear pre-synaptic and dendritic integration is considered to be responsible for nonlinear computation power of biological neurons, emphasizing the role of nonl…

cs.NE2015★ 4 cited

Product Reservoir Computing: Time-Series Computation with Multiplicative Neurons

Alireza Goudarzi, Alireza Shabani, Darko Stefanovic

Echo state networks (ESN), a type of reservoir computing (RC) architecture, are efficient and accurate artificial neural systems for time series processing and learning. An ESN con…