Publications related to Practical issues with modeling extreme Brazilian rainfall

Adversarial Parametric Pose Prior

Pascal Fua, Mathieu Salzmann, Anastasia Remizova, Andrey Davydov, Victor Constantin, Sina Honari

The Skinned Multi-Person Linear (SMPL) model represents human bodies by mapping pose and shape parameters to body meshes. However, not all pose and shape parameter values yield physically-plausible or even realistic body meshes. In other words, SMPL is und ...

IEEE2022

Meta-Learners for Estimation of Causal Effects: Finite Sample Cross-Fit Performance

Gabriel Okasa

Estimation of causal effects using machine learning methods has become an active research field in econometrics. In this paper, we study the finite sample performance of meta-learners for estimation of heterogeneous treatment effects under the usage of sam ...

2022

Revisiting the Calculation of the Early Time HEMP Conducted Environment

Carlos Alberto Romero Romero, Nicolas Mora Parra

The early time high altitude electromagnetic pulse conducted environment calculation is revisited by using the transmission line (TL) theory and including high-frequency corrections that were not present in the earlier studies. Waveform salient parameters, ...

2021

The challenges of impact evaluation: Attempting to measure the effectiveness of community-based disaster risk management

Anthony Christopher Davison, Nicola Mary Banwell, Silvia Hostettler, Alfredo Rafael Kägi Trejo

Although disaster risk management is becoming increasingly important in development cooperation, there is still a lack of robust evidence regarding its effectiveness. Few studies based on a counterfactual have been conducted in the fields of disaster manag ...

2020

Parameter Determination of Sensor Stochastic Models under Covariate Dependency

Jan Skaloud, Stéphane Guerrier, Philipp Clausen

The proliferation of (low-cost) sensors provokes new challenges in data fusion. This is related to the correctness of stochastic characterization that is a prerequisite for optimal estimation of parameters from redundant observations. Different (statistica ...

2017

Structural estimation for route choice models considering link specificity of measurement error variances

Yuki Oyama

For estimating parameters of discrete choice models, observations corresponding to the models are required. In the context of route choice models, we need the information of paths, which are sequences of links and connect between the origin-destination pa ...

2017

The STM bias voltage-dependent polymorphism of a binary supramolecular network

Klaus Kern, Magalí Alejandra Lingenfelder, Fernando Pablo Cometto, Bart Willem Stel, Kilian Frank

A Scanning Tunneling Microscope (STM) is used to induce a reversible transition between different polymorphs in a binary supramolecular network at the liquid/solid interface. The transition is driven externally by switching the polarity of the sample by po ...

Royal Society of Chemistry2017

Renormalization and blow up for wave maps from $S^2 \times \mathbb{R}$ to $S^2$

Sohrab Mirshams Shahshahani

We construct a one parameter family of nite time blow ups to the co-rotational wave maps problem from

S^2\times R

to

S^2

parameterized by

\nu \epsilon (\frac{1}{2},1]

. The longitudinal function

u(t,\alpha)

which is the main object of study will be ...

2016

RENORMALIZATION AND BLOW-UP FOR WAVE MAPS FROM S-2 x R TO S-2

Sohrab Mirshams Shahshahani

We construct a one parameter family of finite time blow-ups to the co-rotational wave maps problem from S-2 x R to S-2, parameterized by nu is an element of (1/2, 1]. The longitudinal function u(t, alpha) which is the main object of study will be obtained ...

American Mathematical Society2016

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

Practical issues with modeling extreme Brazilian rainfall

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Adversarial Parametric Pose Prior

Meta-Learners for Estimation of Causal Effects: Finite Sample Cross-Fit Performance

Revisiting the Calculation of the Early Time HEMP Conducted Environment

The challenges of impact evaluation: Attempting to measure the effectiveness of community-based disaster risk management

Parameter Determination of Sensor Stochastic Models under Covariate Dependency

Structural estimation for route choice models considering link specificity of measurement error variances

The STM bias voltage-dependent polymorphism of a binary supramolecular network

Renormalization and blow up for wave maps from $S^2 \times \mathbb{R}$ to $S^2$

RENORMALIZATION AND BLOW-UP FOR WAVE MAPS FROM S-2 x R TO S-2

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

Adversarial Parametric Pose Prior

Structural estimation for route choice models considering link specificity of measurement error variances

Renormalization and blow up for wave maps from $S^2 \times \mathbb{R}$ to $S^2$

Revisiting the Calculation of the Early Time HEMP Conducted Environment

Parameter Determination of Sensor Stochastic Models under Covariate Dependency

The STM bias voltage-dependent polymorphism of a binary supramolecular network

Meta-Learners for Estimation of Causal Effects: Finite Sample Cross-Fit Performance

The challenges of impact evaluation: Attempting to measure the effectiveness of community-based disaster risk management

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

RENORMALIZATION AND BLOW-UP FOR WAVE MAPS FROM S-2 x R TO S-2