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Concept

Expected value

Related publications (28)

A quantum algorithm for the direct estimation of the steady state of open quantum systems

Vincenzo Savona

Simulating the dynamics and the non-equilibrium steady state of an open quantum system are hard computational tasks on conventional computers. For the simulation of the time evolution, several efficient quantum algorithms have recently been developed. Howe ...

2021

Data-Aware Privacy-Preserving Machine Learning

Aleksei Triastcyn

In this thesis, we focus on the problem of achieving practical privacy guarantees in machine learning (ML), where the classic differential privacy (DP) fails to maintain a good trade-off between user privacy and data utility. Differential privacy guarantee ...

EPFL2020

The Almost-Sure Asymptotic Behavior Of The Solution To The Stochastic Heat Equation With Levy Noise

Carsten Hao Ye Chong

We examine the almost-sure asymptotics of the solution to the stochastic heat equation driven by a Levy space-time white noise. When a spatial point is fixed and time tends to infinity, we show that the solution develops unusually high peaks over short tim ...

INST MATHEMATICAL STATISTICS2020

Shapes of rotating normal fluid He-3 versus superfluid He-4 droplets in molecular beams

Christoph Bostedt, Andre Al Haddad

Previous single-pulse extreme ultraviolet and x-ray coherent diffraction studies revealed that superfluid He-4 droplets obtained in a free jet expansion acquire sizable angular momentum, resulting in significant centrifugal distortion. Similar experiments ...

AMER PHYSICAL SOC2020

Amplitude analysis for the measurement of the photon polarisation in B rightarrow K pi pi gamma decays

Violaine Bellée

This work proposes a method to measure the photon polarisation in

B^+ \rightarrow K^+ \pi^- \pi^+ \gamma

decays and prepares the necessary elements for this measurement using the data sets collected by the LHCb experiment at CERN in

2011

2012

, $2016 ...

EPFL2020

Neural Correlates of Reinforcement Learning: eligibility trace, reward prediction error, novelty and surprise

He Xu

In reinforcement learning (RL), an agent makes sequential decisions to maximise the reward it can obtain from an environment. During learning, the actual and expected outcomes are compared to tell whether a decision was good or bad. The difference between ...

EPFL2020

DWI Simulation-Assisted Machine Learning Models for Microstructure Estimation

Jean-Philippe Thiran, Gabriel Girard, Erick Jorge Canales Rodriguez, Muhamed Barakovic, Marco Pizzolato, Jonathan Rafael Patino Lopez, Thomas Yu

Diffusion MRI (DW-MRI) allows for the detailed exploration of the brain white matter microstructure, with applications in both research and the clinic. However, state-of-the-art methods for microstructure estimation suffer from known limitations, such as t ...

Springer Nature2020

Constrained expectation-maximization algorithm for stochastic inertial error modeling: study of feasibility

Jan Skaloud, Stéphane Guerrier, Yannick Stebler

Stochastic modeling is a challenging task for low-cost sensors whose errors can have complex spectral structures. This makes the tuning process of the INS/GNSS Kalman filter often sensitive and difficult. For example, first-order Gauss–Markov processes are ...

IOP Publishing2011

Related publications (28)

B^+ \rightarrow K^+ \pi^- \pi^+ \gamma

decays and prepares the necessary elements for this measurement using the data sets collected by the LHCb experiment at CERN in

2011

2012

, $2016 ...

EPFL2020