Publications related to Maximum likelihood estimation

Momentum-Based Policy Gradient with Second-Order Information

Patrick Thiran, Negar Kiyavash, Mohammadsadegh Khorasani, Saber Salehkaleybar

Variance-reduced gradient estimators for policy gradient methods have been one of the main focus of research in the reinforcement learning in recent years as they allow acceleration of the estimation process. We propose a variance-reduced policy-gradient m ...

2022

GaSLAM: An Algorithm for Simultaneous Gas Source Localization and Gas Distribution Mapping in 3D

Alcherio Martinoli, Chiara Ercolani, Lixuan Tang

Chemical gas dispersion poses considerable threat to humans, animals and the environment. The research areas of gas source localization and gas distribution mapping aim to localize the source of gas leaks and map the gas plume respectively, in order to hel ...

2022

Drift Estimation of Multiscale Diffusions Based on Filtered Data

Assyr Abdulle, Giacomo Garegnani, Andrea Zanoni, Grigorios A. Pavliotis

We study the problem of drift estimation for two-scale continuous time series. We set ourselves in the framework of overdamped Langevin equations, for which a single-scale surrogate homogenized equation exists. In this setting, estimating the drift coeffic ...

2021

MATHICSE Technical Report : Analysis-aware defeaturing: problem setting and a posteriori estimation

Annalisa Buffa, Rafael Vazquez Hernandez, Ondine Gabrielle Chanon

Defeaturing consists in simplifying geometrical models by removing the geometrical features that are considered not relevant for a given simulation. Feature removal and simplification of computer-aided design models enables faster simulations for engineeri ...

EPFL2021

Fundamental bounds on the precision of iSCAT, COBRI and dark-field microscopy for 3D localization and mass photometry

Jonathan Yuelin Dong

Interferometric imaging is an emerging technique for particle tracking and mass photometry. Mass or position are estimated from weak signals, coherently scattered from nanoparticles or single molecules, and interfered with a co-propagating reference. In th ...

IOP PUBLISHING LTD2021

A Modular Workflow for Model Building, Analysis, and Parameter Estimation in Systems Biology and Neuroscience

Daniel Keller, Andrii Stepaniuk

Neuroscience incorporates knowledge from a range of scales, from single molecules to brain wide neural networks. Modeling is a valuable tool in understanding processes at a single scale or the interactions between two adjacent scales and researchers use a ...

HUMANA PRESS INC2021

Separating Algorithms From Questions and Causal Inference With Unmeasured Exposures: An Application to Birth Cohort Studies of Early Body Mass Index Rebound

Mats Julius Stensrud, Aaron Leor Sarvet

Observational studies reporting on adjusted associations between childhood body mass index (BMI; weight (kg)/height (m)(2)) rebound and subsequent cardiometabolic outcomes have often not paid explicit attention to causal inference, including definition of ...

2021

Experimental assessment of traffic density estimation at link and network level with sparse data

Nikolaos Geroliminis, Anna Takayasu

This paper investigates the accuracy of mean density estimation from direct sensing at link and network levels. Different calculation methods are compared depending on sensor type, probe vehicles or loop detectors, and availability to quantify the magnitud ...

TAYLOR & FRANCIS LTD2021

A probabilistic finite element method based on random meshes: A posteriori error estimators and Bayesian inverse problems

Assyr Abdulle, Giacomo Garegnani

We present a novel probabilistic finite element method (FEM) for the solution and uncertainty quantification of elliptic partial differential equations based on random meshes, which we call random mesh FEM (RM-FEM). Our methodology allows to introduce a pr ...

ELSEVIER SCIENCE SA2021

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Maximum likelihood estimation

Momentum-Based Policy Gradient with Second-Order Information

GaSLAM: An Algorithm for Simultaneous Gas Source Localization and Gas Distribution Mapping in 3D

Bayesian Methods for the Identification of Distribution Networks

Drift Estimation of Multiscale Diffusions Based on Filtered Data

MATHICSE Technical Report : Analysis-aware defeaturing: problem setting and a posteriori estimation

Fundamental bounds on the precision of iSCAT, COBRI and dark-field microscopy for 3D localization and mass photometry

A Modular Workflow for Model Building, Analysis, and Parameter Estimation in Systems Biology and Neuroscience

Separating Algorithms From Questions and Causal Inference With Unmeasured Exposures: An Application to Birth Cohort Studies of Early Body Mass Index Rebound

Experimental assessment of traffic density estimation at link and network level with sparse data

A probabilistic finite element method based on random meshes: A posteriori error estimators and Bayesian inverse problems

Graph Chatbot

Chat with Graph Search

Bayesian Methods for the Identification of Distribution Networks

A Modular Workflow for Model Building, Analysis, and Parameter Estimation in Systems Biology and Neuroscience

Fundamental bounds on the precision of iSCAT, COBRI and dark-field microscopy for 3D localization and mass photometry

Drift Estimation of Multiscale Diffusions Based on Filtered Data

MATHICSE Technical Report : Analysis-aware defeaturing: problem setting and a posteriori estimation

GaSLAM: An Algorithm for Simultaneous Gas Source Localization and Gas Distribution Mapping in 3D

A probabilistic finite element method based on random meshes: A posteriori error estimators and Bayesian inverse problems

Momentum-Based Policy Gradient with Second-Order Information

Separating Algorithms From Questions and Causal Inference With Unmeasured Exposures: An Application to Birth Cohort Studies of Early Body Mass Index Rebound

Experimental assessment of traffic density estimation at link and network level with sparse data