11 citations · 14 across the 7 of their papers we have counts for
8 papers
Universal Approximation in Dropout Neural Networks
Oxana A. Manita, Mark A. Peletier, Jacobus W. Portegies +2
We prove two universal approximation theorems for a range of dropout neural networks. These are feed-forward neural networks in which each edge is given a random -valued f…
Asymptotic convergence rate of Dropout on shallow linear neural networks
Albert Senen-Cerda, Jaron Sanders
We analyze the convergence rate of gradient flows on objective functions induced by Dropout and Dropconnect, when applying them to shallow linear Neural Networks (NNs) - which can…
Modeling Rydberg Gases using Random Sequential Adsorption on Random Graphs
Daan Rutten, Jaron Sanders
The statistics of strongly interacting, ultracold Rydberg gases are governed by the interplay of two factors: geometrical restrictions induced by blockade effects, and quantum mech…
Markov chains and hitting times for error accumulation in quantum circuits
Long Ma, Jaron Sanders
We study a classical model for the accumulation of errors in multi-qubit quantum computations. By modeling the error process in a quantum computation using two coupled Markov chain…
Sub-Poissonian Statistics of Jamming Limits in Ultracold Rydberg Gases
Jaron Sanders, Matthieu Jonckheere, Servaas Kokkelmans
Several recent experiments have established by measuring the Mandel Q parameter that the number of Rydberg excitations in ultracold gases exhibits sub-Poissonian statistics. This e…
Scaling limits for exploration algorithms
Paola Bermolen, Matthieu Jonckheere, Jaron Sanders
We consider an exploration algorithm where at each step, a random number of items become active while related items get explored. Given an initial number of items growing to in…