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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
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Posts
blog
It Is Necessary to Combine Batch Normalization and Skip Connections
Published:
Overview of my research published in ICML 2019.
[Link] to blog post in Towards Data Science.
Disclaimer: For ease of exposition, some notations have been simplified compared to the original notations from the paper.
The Serendipitous Effectiveness of Weight Decay in Deep Learning
Published:
[Link] to blog post in Towards Data Science.
Removing Batch Dependence in CNNs by Proxy-Normalizing Activations
Published:
[Link] to blog post in Towards Data Science.
portfolio
BAOlab: Baryon Acoustic Oscillations Software
Published:
C++ toolbox for the statistical analysis of galaxy surveys.
[Link]
Nomad: Solution for the Challenge ”nomad2018 predicting transparent conductors” (using CNNs, SVR + Model Stacking)
Published:
[Link] to readme and source.
Optim-PV-Battery: Solution for the Challenge ”power laws: optimizing demand-side strategies” (using DQNs, Policy Networks)
Published:
[Link] to readme and source.
Moments-DNNs: Code for the Paper “Characterizing Well-Behaved vs. Pathological Deep Neural Networks“
Published:
[Link] to readme and source.
publications
Uncertainty in Two-Point Correlation Function Estimators
Published in Astronomical Data Analysis VI, 2010
[Paper]
Statistical Study of the Galaxy Distribution
Published in In Advances in Modern Cosmology, InTech, 2011
[Chapter]
Effect of Model-Dependent Covariance Matrix for Studying Baryon Acoustic Oscillations
Published in In Astronomical Data Analysis VII, 2012
A New Method for Detecting Baryon Acoustic Oscillations
Published in In 47th Rencontres de Moriond on Cosmology, 2012
[Paper]
Effect of Model-Dependent Covariance Matrix for Studying Baryon Acoustic Oscillations
Published in ApJ, 760(2):97, 2012
[Paper]
Detecting Baryon Acoustic Oscillations
Published in ApJ, 746(2):172, 2012
[Paper]
Uncertainty in Two-Point Correlation Function Estimators and Baryon Acoustic Oscillation Detection in Galaxy Surveys
Published in Statistical Methodology, 9(1-2):85–100, 2012
[Paper]
Wavelet Analysis of Baryon Acoustic Structures in the Galaxy Distribution
Published in A&A, 542:A34, 2012
[Paper]
The Clustering of Galaxies in the SDSS-III Baryon Oscillation Spectroscopic Survey: Cosmological Implications of the Large-Scale Two-Point Correlation Function
Published in MNRAS, 425(1):415–437, 2012
[Paper]
The Clustering of Galaxies in the SDSS-III Baryon Oscillation Spectroscopic Survey: Baryon Acoustic Oscillations in the Data Release 9 Spectroscopic Galaxy Sample
Published in MNRAS, 427(4):3435–3467, 2012
[Paper]
An Optimized Correlation Function Estimator for Galaxy Surveys
Published in A&A, 554:A131, 2013
[Paper]
Characterizing Well-Behaved vs. Pathological Deep Neural Networks
Published in 36th International Conference on Machine Learning (ICML 2019), 2019
[Paper]
Making EfficientNet More Efficient: Exploring Batch-Independent Normalization, Group Convolutions and Reduced Resolution Training
Published in arXiv, 2021
[Paper]
Proxy-Normalizing Activations to Match Batch Normalization while Removing Batch Dependence
Published in 35th Conference on Neural Information Processing Systems (NeurIPS 2021), 2021
[Paper]
talks
Statistique de la Distribution des Galaxies et Analyse Fractale
Published:
Introduction to statistical analysis of the galaxy distribution, with a particular look at fractal analysis.
[Slides in French]
Reliability of Galaxy Correlation Function Estimation - Application to SDSS DR7
Published:
Presentation of my results on the reliability of galaxy correlation function estimators at the conference Astronomical Data Analysis VI.
[Poster]
Uncertainty in Correlation Function Estimators and BAO Detection in Current Galaxy Surveys
Published:
Presentation of my results on uncertainty in correlation function estimators and reliability of BAO detection from my first paper published in Statistical Methodology.
[Slides]
BAO Detection Methods
Published:
Presentation of the state of my research on BAO detection. This research was continued and later published in ApJ.
[Slides]
BAO and SDSS DR7
Published:
Presentation of the state of my research on BAO detection and BAO study with model-dependent covariance matrix. This research was continued and later published in 2 ApJ papers.
[Slides]
A New Method for Detecting BAOs
Published:
Presentation of my results on BAO detection at the conference 47th Rencontres de Moriond.
[Poster]
BAO Study with Model-Dependent Covariance Matrix
Published:
Presentation of my results on BAO study with model-dependent covariance matrix at the conference Astronomical Data Analysis VII.
[Slides]
Etude Statistique des Corrélations dans la Distribution des Galaxies – Application aux Oscillations Baryoniques Acoustiques
Published:
Presentation given for my PhD Defense.
[Slides in French]
Introduction to Machine Learning and Deep Learning
Published:
Presentation on machine learning and deep learning for internal training at PEAT.
[Slides]
Lessons Learned Building an Highly-Specialized Image Recognition System from Scratch
Published:
Talk given at the 8th gathering of Berlin AI with numerous AI professionals.
[Slides]
Characterizing Well-Behaved vs. Pathological Deep Neural Networks
Published:
Presentation of my research on the characterization of deep neural networks at ICML 2019.
[Slides] [Poster]
Disclaimer: For ease of exposition, some notations have been simplified compared to the original notations from the paper.
On the Inductive Bias of Various Architectures of Deep ReLU Nets
Published:
Presentation of my research during a seminar at Imagine Lab, ENPC.
[Slides]
Removing Batch Dependence in the Normalization of CNNs by Proxy-Normalizing Activations
Published:
Presentation of my research on the normalization of CNNs in a Graphcore webinar.
[Slides]
Proxy-Normalizing Activations to Match Batch Normalization while Removing Batch Dependence
Published:
Presentation of my research on Proxy Norm at NeurIPS 2021.
[Slides] [Poster]