Publications related to Dynamics of vortices in disordered Josephson junctions arrays

Sublinear Bounds on the Distinguishing Advantage for Multiple Samples

The maximal achievable advantage of a (computationally unbounded) distinguisher to determine whether a source

Z

is distributed according to distribution

P_0

or

P_1

, when given access to one sample of

Z

, is characterized by the statistical distance ...

Springer, Cham2020

Wasserstein Distributionally Robust Learning

Soroosh Shafieezadeh Abadeh

Many decision problems in science, engineering, and economics are affected by uncertainty, which is typically modeled by a random variable governed by an unknown probability distribution. For many practical applications, the probability distribution is onl ...

EPFL2020

Distributional Robustness in Mechanism Design

Cagil Kocyigit

Mechanism design theory examines the design of allocation mechanisms or incentive systems involving multiple rational but self-interested agents and plays a central role in many societally important problems in economics. In mechanism design problems, agen ...

EPFL2020

From Data to Decisions: Distributionally Robust Optimization is Optimal

Daniel Kuhn, Peyman Mohajerin Esfahani

We study stochastic programs where the decision-maker cannot observe the distribution of the exogenous uncertainties but has access to a finite set of independent samples from this distribution. In this setting, the goal is to find a procedure that transfo ...

2020

Collaborative Sampling in Generative Adversarial Networks

Alexandre Massoud Alahi, Yuejiang Liu, Parth Ashit Kothari

The standard practice in Generative Adversarial Networks (GANs) discards the discriminator during sampling. However, this sampling method loses valuable information learned by the discriminator regarding the data distribution. In this work, we propose a co ...

2020

A nonparametric method for producing isolines of bivariate exceedance probabilities

Emeric Rolland Georges Thibaud

We present a method for drawing isolines indicating regions of equal joint exceedance probability for bivariate data. The method relies on bivariate regular variation, a dependence framework widely used for extremes. The method we utilize for characterizin ...

SPRINGER2019

An Alternate Statistical Lens to Look at Collaboration Data: Extreme Value Theory

Kshitij Sharma, Jennifer Kaitlyn Olsen

To provide beneficial feedback to students during their collaboration, it is important to identify behaviors that are indicative of good collaboration. However, in a collaborative learning session, students engage in a range of behaviors and it can be diff ...

2019

Numerical Analysis of the Influence of Surface Roughness on Shear Strength of Cracked Concrete

Guillaume Anciaux, Mohit Pundir

Aggregate interlock is the mechanism via which normal and shear stresses are transferred across the lips of cracks in concrete . The fractal property of cracking surfaces in concrete plays a significant role in shear transfer across surfaces. Because of th ...

2019

TiD-Introducing and Benchmarking an Event-Delivery System for Brain-Computer Interfaces

Robert Leeb, Michele Tavella

In this paper, we present and analyze an event distribution system for brain-computer interfaces. Events are commonly used to mark and describe incidents during an experiment and are therefore critical for later data analysis or immediate real-time process ...

Institute of Electrical and Electronics Engineers2017

Bayesian Calibration of Thermal-Hydraulics Model with Time-Dependent Output

Andreas Pautz, Damar Canggih Wicaksono, Omar Zerkak

The currently adopted practice for uncertainty quantification of thermal-hydraulics code predictions is done through statistical sampling where the code is evaluated multiple times using different values of input parameters that are randomly generated acco ...

2016

Dynamics of vortices in disordered Josephson junctions arrays

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Sublinear Bounds on the Distinguishing Advantage for Multiple Samples

Wasserstein Distributionally Robust Learning

Distributional Robustness in Mechanism Design

From Data to Decisions: Distributionally Robust Optimization is Optimal

Collaborative Sampling in Generative Adversarial Networks

A nonparametric method for producing isolines of bivariate exceedance probabilities

An Alternate Statistical Lens to Look at Collaboration Data: Extreme Value Theory

Numerical Analysis of the Influence of Surface Roughness on Shear Strength of Cracked Concrete

TiD-Introducing and Benchmarking an Event-Delivery System for Brain-Computer Interfaces

Bayesian Calibration of Thermal-Hydraulics Model with Time-Dependent Output

Wasserstein Distributionally Robust Learning

Sublinear Bounds on the Distinguishing Advantage for Multiple Samples

A nonparametric method for producing isolines of bivariate exceedance probabilities

Distributional Robustness in Mechanism Design

An Alternate Statistical Lens to Look at Collaboration Data: Extreme Value Theory

Numerical Analysis of the Influence of Surface Roughness on Shear Strength of Cracked Concrete

From Data to Decisions: Distributionally Robust Optimization is Optimal

Collaborative Sampling in Generative Adversarial Networks

TiD-Introducing and Benchmarking an Event-Delivery System for Brain-Computer Interfaces

Bayesian Calibration of Thermal-Hydraulics Model with Time-Dependent Output