Publications related to Law of large numbers

Forbidden induced subposets of given height

Let P be a partially ordered set. The function La* (n, P) denotes the size of the largest family F subset of 2([n]) that does not contain an induced copy of P. It was proved by Methuku and Palvolgyi that there exists a constant C-P (depending only on P) su ...

ACADEMIC PRESS INC ELSEVIER SCIENCE2019

Variational Quantum Monte Carlo Method with a Neural-Network Ansatz for Open Quantum Systems

Vincenzo Savona, Alexandra Nagy

The possibility to simulate the properties of many-body open quantum systems with a large number of degrees of freedom (d.o.f.) is the premise to the solution of several outstanding problems in quantum science and quantum information. The challenge posed b ...

AMER PHYSICAL SOC2019

Free standing and solidly mounted Lamb wave resonators based on Al0.85Sc0.15N thin film

Paul Muralt, Mohammad Fazel Parsapour Kolour, Vladimir Pashchenko

Lamb wave microresonators with wavelengths of 5-8m, vibrating in the S0 mode, and having 75 electrode pairs were fabricated and characterized. The results were compared to theoretical predictions obtained by finite element simulation. The active material w ...

AMER INST PHYSICS2019

Comparing dynamics: deep neural networks versus glassy systems

Matthieu Wyart, Mario Geiger, Marco Baity-Jesi, Stefano Spigler, Levent Dogus Sagun

We analyze numerically the training dynamics of deep neural networks (DNN) by using methods developed in statistical physics of glassy systems. The two main issues we address are (1) the complexity of the loss landscape and of the dynamics within it, and ( ...

IOP PUBLISHING LTD2019

MATHICSE Technical Report : Random time step probabilistic methods for uncertainty quantification in chaotic and geometric numerical integration

Assyr Abdulle, Giacomo Garegnani

A novel probabilistic numerical method for quantifying the uncertainty induced by the time integration of ordinary differential equations (ODEs) is introduced. Departing from the classical strategy to randomize ODE solvers by adding a random forcing term, ...

MATHICSE2018

Chebyshev Inequalities for Products of Random Variables

Daniel Kuhn, Napat Rujeerapaiboon, Wolfram Wiesemann

We derive sharp probability bounds on the tails of a product of symmetric non-negative random variables using only information about their first two moments. If the covariance matrix of the random variables is known exactly, these bounds can be computed nu ...

2018

Indiscreet logarithms in finite fields of small characteristic

Robert Granger, Thorsten Kleinjung, Jens Markus Zumbrägel

Recently, several striking advances have taken place regarding the discrete logarithm problem (DLP) in finite fields of small characteristic, despite progress having remained essentially static for nearly thirty years, with the best known algorithms being ...

2018

Comparing Dynamics: Deep Neural Networks versus Glassy Systems

Mario Geiger, Marco Baity-Jesi, Rainer Wesche, Stefano Spigler, Levent Dogus Sagun

We analyze numerically the training dynamics of deep neural networks (DNN) by using methods developed in statistical physics of glassy systems. The two main issues we address are the complexity of the loss-landscape and of the dynamics within it, and to wh ...

2018

Shape constrained splines as transparent black-box models for bioprocess modeling

Dominique Bonvin, Julien Léo Billeter, Sriniketh Srinivasan

Empirical model identification for biological systems is a challenging task due to the combined effects of complex interactions, nonlinear effects, and lack of specific measurements. In this context, several researchers have provided tools for experimental ...

Elsevier2017

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Law of large numbers

Forbidden induced subposets of given height

Variational Quantum Monte Carlo Method with a Neural-Network Ansatz for Open Quantum Systems

Free standing and solidly mounted Lamb wave resonators based on Al0.85Sc0.15N thin film

Efficient Relaxations for Dense CRFs with Sparse Higher-Order Potentials

Comparing dynamics: deep neural networks versus glassy systems

MATHICSE Technical Report : Random time step probabilistic methods for uncertainty quantification in chaotic and geometric numerical integration

Chebyshev Inequalities for Products of Random Variables

Indiscreet logarithms in finite fields of small characteristic

Comparing Dynamics: Deep Neural Networks versus Glassy Systems

Shape constrained splines as transparent black-box models for bioprocess modeling

Graph Chatbot

Chat with Graph Search

Forbidden induced subposets of given height

Indiscreet logarithms in finite fields of small characteristic

MATHICSE Technical Report : Random time step probabilistic methods for uncertainty quantification in chaotic and geometric numerical integration

Free standing and solidly mounted Lamb wave resonators based on Al0.85Sc0.15N thin film

Efficient Relaxations for Dense CRFs with Sparse Higher-Order Potentials

Comparing dynamics: deep neural networks versus glassy systems

Variational Quantum Monte Carlo Method with a Neural-Network Ansatz for Open Quantum Systems

Comparing Dynamics: Deep Neural Networks versus Glassy Systems

Shape constrained splines as transparent black-box models for bioprocess modeling

Chebyshev Inequalities for Products of Random Variables