Rémi Bardenet

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Monte Carlo Methods

Rémi Bardenet, 2018, Encyclopedia of Social Network Analysis and Mining. 2nd Ed..

Ten Simple Rules for a Successful Cross-Disciplinary Collaboration

Alexander G. Fletcher, Charlotte M. Deane, David Gavaghan, 2015, PLoS Comput. Biol..

Adaptive Metropolis with Online Relabeling

Gersende Fort, Balázs Kégl, Olivier Cappé, 2012, AISTATS.

Robust cell tracking in epithelial tissues through identification of maximum common subgraphs

Ruth E. Baker, Alexander G. Fletcher, Rémi Bardenet, 2016, bioRxiv.

DPPy: DPP Sampling with Python

Michal Valko, Rémi Bardenet, Guillermo Polito, 2019, J. Mach. Learn. Res..

Uncertainty and variability in models of the cardiac action potential: Can we build trustworthy models?

Pras Pathmanathan, Gary R. Mirams, Rémi Bardenet, 2016, Journal of molecular and cellular cardiology.

On Markov chain Monte Carlo methods for tall data

Arnaud Doucet, Rémi Bardenet, Christopher C. Holmes, 2015, J. Mach. Learn. Res..

Monte Carlo Methods

Rémi Bardenet, R. Bardenet, 2013, Encyclopedia of Social Network Analysis and Mining. 2nd Ed..

Towards adaptive learning and inference - Applications to hyperparameter tuning and astroparticle physics

Rémi Bardenet, R. Bardenet, 2012 .

From Random Matrices to Monte Carlo Integration Via Gaussian Quadrature

Rémi Bardenet, Adrien Hardy, A. Hardy, 2018, 2018 IEEE Statistical Signal Processing Workshop (SSP).

Towards scaling up Markov chain Monte Carlo: an adaptive subsampling approach

Arnaud Doucet, Rémi Bardenet, Christopher C. Holmes, 2014, ICML.

DPPy: Sampling Determinantal Point Processes with Python pdf

Michal Valko, Rémi Bardenet, Guillaume Gautier, 2018, ArXiv.

Surrogating the surrogate: accelerating Gaussian-process-based global optimization with a mixture cross-entropy algorithm

Balázs Kégl, Rémi Bardenet, B. Kégl, 2010, ICML.

A determinantal point process for column subset selection pdf

Pierre Chainais, Rémi Bardenet, Ayoub Belhadji, 2018, J. Mach. Learn. Res..

Robust cell tracking in epithelial tissues through identification of maximum common subgraphs

Rémi Bardenet, Ruth E Baker, Jochen Kursawe, 2016, bioRxiv.

On two ways to use determinantal point processes for Monte Carlo integration

Michal Valko, Rémi Bardenet, Guillaume Gautier, 2019, NeurIPS.

On a few statistical applications of determinantal point processes

Rémi Bardenet, Frédéric Lavancier, Xavier Mary, 2017 .

Algorithms for Hyper-Parameter Optimization

Yoshua Bengio, Balázs Kégl, Rémi Bardenet, 2011, NIPS.

A note on replacing uniform subsampling by random projections in MCMC for linear regression of tall datasets

Rémi Bardenet, Odalric-Ambrym Maillard, Odalric-Ambrym Maillard, 2015 .

Hierarchical Bayesian inference for ion channel screening dose-response data

Gary R. Mirams, Rémi Bardenet, David J Gavaghan, 2016, Wellcome open research.

Inference for determinantal point processes without spectral knowledge

Rémi Bardenet, Michalis K. Titsias, 2015, NIPS.

Hierarchical Bayesian modelling of variability and uncertainty in synthetic action potential traces

David Gavaghan, Mark Davies, Liudmila Polonchuk, 2016, 2016 Computing in Cardiology Conference (CinC).

A correspondence between zeros of time-frequency transforms and Gaussian analytic functions

Pierre Chainais, Rémi Bardenet, Julien Flamant, 2019, 2019 13th International conference on Sampling Theory and Applications (SampTA).

Collaborative hyperparameter tuning

Michèle Sebag, Balázs Kégl, Mátyás Brendel, 2013, ICML.

Zonotope Hit-and-run for Efficient Sampling from Projection DPPs

Michal Valko, Rémi Bardenet, Guillaume Gautier, 2017, ICML.

CONSTRAINTS ON THE ORIGIN OF COSMIC RAYS ABOVE 1018 eV FROM LARGE-SCALE ANISOTROPY SEARCHES IN DATA OF THE PIERRE AUGER OBSERVATORY

S. Fliescher, Octavian Fratu, Balázs Kégl, 2012 .

The Pierre Auger Collaboration

S. Fliescher, M. C. Maccarone, Martin Erdmann, 2011 .

Sinusoidal voltage protocols for rapid characterisation of ion channel kinetics

Jamie I. Vandenberg, Adam P. Hill, Gary R. Mirams, 2017, bioRxiv.

Sinusoidal voltage protocols for rapid characterization of ion channel kinetics

Jamie I. Vandenberg, Adam P. Hill, Gary R. Mirams, 2017, bioRxiv.

An adaptive Monte-Carlo Markov chain algorithm for inference from mixture signals

Balázs Kégl, Rémi Bardenet, B. Kégl, 2012 .

Large scale distribution of arrival directions of cosmic rays detected above $10^{18}$ eV at the Pierre Auger Observatory

S. Fliescher, Octavian Fratu, Balázs Kégl, 2012 .

Ultrahigh Energy Neutrinos at the Pierre Auger Observatory

S. Fliescher, Octavian Fratu, Balázs Kégl, 2013, 1304.1630.

An Adaptive Subsampling Approach for MCMC Inference in Large Datasets

Arnaud Doucet, Chris Holmes, Rémi Bardenet, 2014 .