Patricia Reynaud-Bouret
French mathematician
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Mathematics
Patricia Reynaud-Bouret's Degrees
- PhD Mathematics Université Paris Cité
- Masters Mathematics Université Paris Cité
- Bachelors Mathematics Université Paris Cité
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Why Is Patricia Reynaud-Bouret Influential?
(Suggest an Edit or Addition)According to Wikipedia, Patricia Reynaud-Bouret is a French statistician who has studied Hawkes processes, density estimation, and concentration inequalities, and applied them in neuroscience, neural connectivity reconstruction, and genomics. She is a director of research for the French National Centre for Scientific Research , affiliated with the J. A. Dieudonné Laboratory of Côte d'Azur University , founder and former director of the university's NeuroMod Institute for Modeling in Neuroscience and Cognition, and a chair holder in the university's Interdisciplinary Institute for Artificial Intelligence .
Patricia Reynaud-Bouret's Published Works
Published Works
- Adaptive estimation for Hawkes processes; application to genome analysis (2009) (208)
- Lasso and probabilistic inequalities for multivariate point processes (2012) (172)
- Exponential Inequalities, with Constants, for U-statistics of Order Two (2003) (104)
- Goodness-of-Fit Tests and Nonparametric Adaptive Estimation for Spike Train Analysis (2014) (103)
- Inference of functional connectivity in Neurosciences via Hawkes processes (2013) (97)
- Microscopic approach of a time elapsed neural model (2015) (67)
- Nonparametric Estimation of the Division Rate of a Size-Structured Population (2011) (66)
- Adaptive density estimation: a curse of support? ✩ (2009) (60)
- Adaptive estimation of the intensity of inhomogeneous Poisson processes via concentration inequalities (2003) (56)
- Near optimal thresholding estimation of a Poisson intensity on the real line (2008) (50)
- Penalized projection estimators of the Aalen multiplicative intensity (2006) (43)
- Some non asymptotic tail estimates for Hawkes processes (2007) (36)
- Kernels Based Tests with Non-asymptotic Bootstrap Approaches for Two-sample Problems (2012) (33)
- Optimal Change-Point Detection and Localization (2020) (29)
- The two-sample problem for Poisson processes: adaptive tests with a non-asymptotic wild bootstrap approach (2012) (29)
- Bootstrap and permutation tests of independence for point processes (2014) (28)
- Reconstructing the functional connectivity of multiple spike trains using Hawkes models (2017) (27)
- Multiple Tests Based on a Gaussian Approximation of the Unitary Events Method with Delayed Coincidence Count (2012) (26)
- A Data-Dependent Weighted LASSO Under Poisson Noise (2015) (22)
- Optimal Kernel Selection for Density Estimation (2015) (16)
- Compensator and exponential inequalities for some suprema of counting processes (2006) (10)
- Spike trains as (in)homogeneous Poisson processes or Hawkes processes: non-parametric adaptive estimation and goodness-of-fit tests (2013) (9)
- Adaptive tests of homogeneity for a Poisson process (2009) (8)
- Family-Wise Separation Rates for multiple testing (2016) (8)
- High Dimensional Probability VII : The Cargèse Volume (2016) (8)
- Concentration for Norms of Infinitely Divisible Vectors With Independent Components (2006) (7)
- Surrogate Data Methods Based on a Shuffling of the Trials for Synchrony Detection: The Centering Issue (2016) (7)
- Sparse space–time models: Concentration inequalities and Lasso (2018) (6)
- Event-Scheduling Algorithms with Kalikow Decomposition for Simulating Potentially Infinite Neuronal Networks (2019) (6)
- Calibration of thresholding rules for Poisson intensity estimation (2009) (6)
- Adaptive thresholding estimation of a Poisson intensity with infinite support (2008) (5)
- Goodness-of-Fit Tests and Nonparametric Adaptive Estimation for Spike Train Analysis (2014) (4)
- Towards a mathematical definition of functional connectivity (2021) (4)
- Exponential Inequalities for U-Statistics of Order Two with Constants (2002) (4)
- Continuous testing for Poisson process intensities: a new perspective on scanning statistics (2017) (4)
- CONCENTRATION INEQUALITIES, COUNTING PROCESSES AND ADAPTIVE STATISTICS (2014) (3)
- Scalability of large neural network simulations via activity tracking with time asynchrony and procedural connectivity (2022) (3)
- Concentration for Infinitely Divisible Vectors with Independent Components (2006) (3)
- Hold-out strategy for selecting learning models: Application to categorization subjected to presentation orders (2022) (2)
- Efficient Simulation of Sparse Graphs of Point Processes (2022) (2)
- Exponential Inequalities for Counting Processes (2002) (2)
- An order-dependent transfer model in categorization (2022) (2)
- Simulation scalability of large brain neuronal networks thanks to time asynchrony (2021) (2)
- Discrete event simulation of point processes: A computational complexity analysis on sparse graphs (2020) (1)
- Completeness period analysis of SisFrance macroseismic database and interpretation in the light of historical context (2014) (1)
- Exponential inequality for chaos based on sampling without replacement (2018) (1)
- Kalikow decomposition for counting processes with stochastic intensity and application to simulation algorithms (2021) (1)
- A Distribution Free Unitary Events Method based on Delayed Coincidence Count (2015) (1)
- Neural Coding as a Statistical Testing Problem (2022) (0)
- Provable local learning rule by expert aggregation for a Hawkes network (2023) (0)
- Multiple independence tests for point processes by permutation methods : a Unitary Events approach based on delayed coincidence count (2015) (0)
- Genomic transcription regulatory element location analysis via poisson weighted lasso (2016) (0)
- Sliding Window Strategy for Convolutional Spike Sorting with Lasso (2021) (0)
- Estimation of local independence graphs via Hawkes processes to unravel functional neuronal connectivity ∗ (2015) (0)
- A concentration inequality for inhomogeneous Neyman–Scott point processes (2019) (0)
- Modeling and Computation of a liquid-vapor bubble formation (2019) (0)
- Large scale Lasso with windowed active set for convolutional spike sorting (2019) (0)
- Editorial for the special issue on Statistics and Neurosciences (2016) (0)
- Investigating interactions between types of order in categorization (2022) (0)
- atlas project – The team (B1) “from Applications to Theory in Learning and Adaptive Statistics” (2006) (0)
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