What is he best known for?
The fields of study he is best known for:
- Mathematical analysis
- Statistics
- Probability theory
His main research concerns Large deviations theory, Mathematical analysis, Mathematical optimization, Stochastic process and Brownian motion.
His Large deviations theory research incorporates themes from Asymptotically optimal algorithm, Markov process, Markov chain and Weak convergence.
His Markov process research integrates issues from Quadratic equation, Laplace's equation and Optimal control.
His work on Stochastic differential equation, Skorokhod problem and Recurrence relation is typically connected to Oblique case and Oblique reflection as part of general Mathematical analysis study, connecting several disciplines of science.
Paul Dupuis combines subjects such as Differential, Rare events, Monte Carlo method, Importance sampling and Robust control with his study of Mathematical optimization.
Paul Dupuis interconnects Infimum and supremum, Combinatorics, Filtration, Bounded function and Calculus in the investigation of issues within Stochastic process.
His most cited work include:
- A weak convergence approach to the theory of large deviations (812 citations)
- Dynamical systems and variational inequalities (332 citations)
- Variational problems on flows of diffeomorphisms for image matching (293 citations)
What are the main themes of his work throughout his whole career to date?
Large deviations theory, Applied mathematics, Mathematical optimization, Rate function and Mathematical analysis are his primary areas of study.
The various areas that he examines in his Large deviations theory study include Stochastic process, Sequence, Markov process and Weak convergence.
His work carried out in the field of Applied mathematics brings together such families of science as Kullback–Leibler divergence, Partial differential equation, Queueing theory, Limit and Upper and lower bounds.
He has included themes like Markov chain and Importance sampling in his Mathematical optimization study.
His Rate function research focuses on subjects like Calculus of variations, which are linked to Combinatorics.
His work on Stochastic differential equation, Laplace principle, Poisson random measure and Lipschitz continuity as part of general Mathematical analysis research is frequently linked to Oblique case, bridging the gap between disciplines.
He most often published in these fields:
- Large deviations theory (33.19%)
- Applied mathematics (28.88%)
- Mathematical optimization (26.72%)
What were the highlights of his more recent work (between 2017-2021)?
- Applied mathematics (28.88%)
- Large deviations theory (33.19%)
- Statistical physics (15.52%)
In recent papers he was focusing on the following fields of study:
Paul Dupuis mostly deals with Applied mathematics, Large deviations theory, Statistical physics, Rate function and Limit.
His Applied mathematics research includes elements of Markov process, Parallel tempering, Of the form, Discrete time and continuous time and Probability measure.
His Large deviations theory study incorporates themes from Sample path, Expected value, Probabilistic logic, Queueing theory and Robustness.
His Statistical physics research incorporates elements of Weak convergence, Brownian motion, Stochastic differential equation, Empirical measure and Monte Carlo method.
His Limit study combines topics in areas such as Sequence and State space.
As a member of one scientific family, Paul Dupuis mostly works in the field of Markov chain, focusing on Type and, on occasion, Mathematical analysis and Dynamical systems theory.
Between 2017 and 2021, his most popular works were:
- Analysis and Approximation of Rare Events : Representations and Weak Convergence Methods (28 citations)
- Large Deviations for Small Noise Diffusions in a Fast Markovian Environment (12 citations)
- Sensitivity analysis for rare events based on Rényi divergence (8 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Mathematical analysis
- Probability theory
Paul Dupuis spends much of his time researching Large deviations theory, Weak convergence, Statistical physics, Rate function and Rare events.
The Large deviations theory study combines topics in areas such as Applied mathematics and Robustness.
His Applied mathematics research includes elements of Probabilistic logic, Queueing theory and Markov process.
His Weak convergence research is multidisciplinary, relying on both Class, Mathematical analysis, Euclidean space, Dual and Empirical measure.
He has researched Statistical physics in several fields, including Sequence and Energy functional.
His work in Rate function addresses subjects such as Stochastic control, which are connected to disciplines such as Limit, State space, Parallel tempering and Brownian motion.
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