Publications | Julien Cornebise, Ph.D.

As of October 2024:

8800+ citations
h-index 16
40+ publications
3 patents

Most of my publications are also available on my Google Scholar profile.

2023

arXiv

Opportunities and Risks of LLMs for Scalable Deliberation with Polis

Christopher T Small, Ivan Vendrov, Esin Durmus, Hadjar Homaei, Elizabeth Barry, Julien Cornebise, Ted Suzman, Deep Ganguli, and Colin Megill

arXiv preprint arXiv:2306.11932, 2023

arXiv Bib PDF

@article{small2023opportunities,
  title = {Opportunities and Risks of {{LLMs}} for Scalable Deliberation with {{Polis}}},
  author = {Small, Christopher T and Vendrov, Ivan and Durmus, Esin and Homaei, Hadjar and Barry, Elizabeth and Cornebise, Julien and Suzman, Ted and Ganguli, Deep and Megill, Colin},
  year = {2023},
  journal = {arXiv preprint arXiv:2306.11932},
  arxiv = {2306.11932},
  google_scholar_id = {BJbdYPG6LGMC}
}

2022

NeurIPS

Open High-Resolution Satellite Imagery: The WorldStrat Dataset–with Application to Super-Resolution

Julien Cornebise, Ivan Oršolić, and Freddie Kalaitzis

Advances in Neural Information Processing Systems (NeurIPS 2022), 2022

arXiv Bib PDF

@article{cornebise2022open,
  title = {Open High-Resolution Satellite Imagery: {{The WorldStrat}} Dataset--with Application to Super-Resolution},
  author = {Cornebise, Julien and Or{\v s}oli{\'c}, Ivan and Kalaitzis, Freddie},
  year = {2022},
  journal = {Advances in Neural Information Processing Systems (NeurIPS 2022)},
  volume = {35},
  pages = {25979--25991},
  arxiv = {2207.06418},
  google_scholar_id = {ZzlSgRqYykMC}
}

Zenodo
The WorldStrat Dataset: Open High-Resolution Satellite Imagery With Paired Multi-Temporal Low-Resolution

Julien Cornebise, Ivan Oršolić, and Freddie Kalaitzis

2022

Abs DOI Bib

What is this dataset? Nearly 10,000 km^2 of free high-resolution and matched low-resolution satellite imagery of unique locations which ensure stratified representation of all types of land-use across the world: from agriculture to ice caps, from forests to multiple urbanization densities. Those locations are also enriched with typically under-represented locations in ML datasets: sites of humanitarian interest, illegal mining sites, and settlements of persons at risk. Each high-resolution image (1.5 m/pixel) comes with multiple temporally-matched low-resolution images from the freely accessible lower-resolution Sentinel-2 satellites (10 m/pixel). We accompany this dataset with a paper, datasheet for datasets and an open-source Python package to: rebuild or extend the WorldStrat dataset, train and infer baseline algorithms, and learn with abundant tutorials, all compatible with the popular EO-learn toolbox. Why make this? We hope to foster broad-spectrum applications of ML to satellite imagery, and possibly develop the same power of analysis allowed by costly private high-resolution imagery from free public low-resolution Sentinel2 imagery. We illustrate this specific point by training and releasing several highly compute-efficient baselines on the task of Multi-Frame Super-Resolution. Licences The high-resolution Airbus imagery is distributed, with authorization from Airbus, under Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0). The labels, Sentinel2 imagery, and trained weights are released under Creative Commons with Attribution 4.0 International (CC BY 4.0). The source code (will be shortly released on GitHub) under 3-Clause BSD license.
@misc{cornebise_worldstrat_2022-1, title = {The {{WorldStrat Dataset}}: {{Open High-Resolution Satellite Imagery With Paired Multi-Temporal Low-Resolution}}}, shorttitle = {The {{WorldStrat Dataset}}}, author = {Cornebise, Julien and Or{\v s}oli{\'c}, Ivan and Kalaitzis, Freddie}, year = {2022}, publisher = {Zenodo}, doi = {10.5281/zenodo.6810792}, urldate = {2024-10-27}, keywords = {image dataset,machine learning,remote sensing,satellite imagery}, file = {/Users/julien/Zotero/storage/2HE3Z35X/Cornebise et al. - 2022 - The WorldStrat Dataset Open High-Resolution Satellite Imagery With Paired Multi-Temporal Low-Resolu.pdf} }

2021

Nature Protocols

Use of Deep Learning to Develop Continuous-Risk Models for Adverse Event Prediction from Electronic Health Records

Nenad Tomašev, Natalie Harris, Sebastien Baur, Anne Mottram, Xavier Glorot, Jack W. Rae, Michal Zielinski, Harry Askham, Andre Saraiva, Valerio Magliulo, Clemens Meyer, Suman Ravuri, Ivan Protsyuk, Alistair Connell, Cían O. Hughes, Alan Karthikesalingam, Julien Cornebise, Hugh Montgomery, Geraint Rees, Chris Laing, Clifton R. Baker, Thomas F. Osborne, Ruth Reeves, Demis Hassabis, Dominic King, Mustafa Suleyman, Trevor Back, Christopher Nielson, Martin G. Seneviratne, Joseph R. Ledsam, and Shakir Mohamed

Nature Protocols, 2021

DOI Bib PDF

@article{tomasev_use_2021,
  title = {Use of Deep Learning to Develop Continuous-Risk Models for Adverse Event Prediction from Electronic Health Records},
  author = {Toma{\v s}ev, Nenad and Harris, Natalie and Baur, Sebastien and Mottram, Anne and Glorot, Xavier and Rae, Jack W. and Zielinski, Michal and Askham, Harry and Saraiva, Andre and Magliulo, Valerio and Meyer, Clemens and Ravuri, Suman and Protsyuk, Ivan and Connell, Alistair and Hughes, C{\'i}an O. and Karthikesalingam, Alan and Cornebise, Julien and Montgomery, Hugh and Rees, Geraint and Laing, Chris and Baker, Clifton R. and Osborne, Thomas F. and Reeves, Ruth and Hassabis, Demis and King, Dominic and Suleyman, Mustafa and Back, Trevor and Nielson, Christopher and Seneviratne, Martin G. and Ledsam, Joseph R. and Mohamed, Shakir},
  year = {2021},
  journal = {Nature Protocols},
  volume = {16},
  number = {6},
  pages = {2765--2787},
  publisher = {Nature Publishing Group UK London},
  urldate = {2024-10-27},
  google_scholar_id = {P7Ujq4OLJYoC},
  url = {https://www-nature-com.libproxy.ucl.ac.uk/articles/s41596-021-00513-5},
  doi = {10.1038/s41596-021-00513-5}
}

2020

arXiv

HighRes-net: Recursive Fusion for Multi-Frame Super-Resolution of Satellite Imagery

Michel Deudon, Alfredo Kalaitzis, Israel Goytom, Md Rifat Arefin, Zhichao Lin, Kris Sankaran, Vincent Michalski, Samira E Kahou, Julien Cornebise, and Yoshua Bengio

arXiv preprint arXiv:2002.06460, 2020

arXiv Bib PDF

@article{deudon2020highres,
  title = {{{HighRes-net}}: {{Recursive}} Fusion for Multi-Frame Super-Resolution of Satellite Imagery},
  author = {Deudon, Michel and Kalaitzis, Alfredo and Goytom, Israel and Arefin, Md Rifat and Lin, Zhichao and Sankaran, Kris and Michalski, Vincent and Kahou, Samira E and Cornebise, Julien and Bengio, Yoshua},
  year = {2020},
  journal = {arXiv preprint arXiv:2002.06460},
  arxiv = {2002.06460},
  google_scholar_id = {yqoGN6RLRZoC},
}

Nature Comm

AI for Social Good: Unlocking the Opportunity for Positive Impact

Nenad Tomašev, Julien Cornebise, Frank Hutter, Shakir Mohamed, Angela Picciariello, Bec Connelly, Danielle C. M. Belgrave, Daphne Ezer, Fanny Cachat Van Der Haert, Frank Mugisha, Gerald Abila, Hiromi Arai, Hisham Almiraat, Julia Proskurnia, Kyle Snyder, Mihoko Otake-Matsuura, Mustafa Othman, Tobias Glasmachers, Wilfried De Wever, Yee Whye Teh, Mohammad Emtiyaz Khan, Ruben De Winne, Tom Schaul, and Claudia Clopath

Nature Communications, 2020

DOI Bib PDF

@article{tomasev2020ai,
  title = {{{AI}} for Social Good: Unlocking the Opportunity for Positive Impact},
  author = {Toma{\v s}ev, Nenad and Cornebise, Julien and Hutter, Frank and Mohamed, Shakir and Picciariello, Angela and Connelly, Bec and Belgrave, Danielle C. M. and Ezer, Daphne and Haert, Fanny Cachat Van Der and Mugisha, Frank and Abila, Gerald and Arai, Hiromi and Almiraat, Hisham and Proskurnia, Julia and Snyder, Kyle and {Otake-Matsuura}, Mihoko and Othman, Mustafa and Glasmachers, Tobias and Wever, Wilfried De and Teh, Yee Whye and Khan, Mohammad Emtiyaz and Winne, Ruben De and Schaul, Tom and Clopath, Claudia},
  year = {2020},
  journal = {Nature Communications},
  volume = {11},
  number = {1},
  pages = {2468},
  publisher = {Nature Publishing Group},
  google_scholar_id = {a3BOlSfXSfwC},
  doi = {10.1038/s41467-020-15871-z},
}

2019

arXiv
DECoVaC: Design of Experiments with Controlled Variability Components

Thomas Boquet, Laure Delisle, Denis Kochetkov, Nathan Schucher, Parmida Atighehchian, Boris Oreshkin, and Julien Cornebise

2019

Abs arXiv Bib PDF

Reproducible research in Machine Learning has seen a salutary abundance of progress lately: workflows, transparency, and statistical analysis of validation and test performance. We build on these efforts and take them further. We offer a principled experimental design methodology, based on linear mixed models, to study and separate the effects of multiple factors of variation in machine learning experiments. This approach allows to account for the effects of architecture, optimizer, hyper-parameters, intentional randomization, as well as unintended lack of determinism across reruns. We illustrate that methodology by analyzing Matching Networks, Prototypical Networks and TADAM on the miniImagenet dataset.
@misc{boquet_decovac_2019, title = {{{DECoVaC}}: {{Design}} of {{Experiments}} with {{Controlled Variability Components}}}, shorttitle = {{{DECoVaC}}}, author = {Boquet, Thomas and Delisle, Laure and Kochetkov, Denis and Schucher, Nathan and Atighehchian, Parmida and Oreshkin, Boris and Cornebise, Julien}, year = {2019}, number = {arXiv:1909.09859}, arxiv = {1909.09859}, publisher = {arXiv}, urldate = {2024-10-27}, keywords = {Computer Science - Artificial Intelligence,Statistics - Methodology}, file = {/Users/julien/Zotero/storage/3TB6XWVV/Boquet et al. - 2019 - DECoVaC Design of Experiments with Controlled Variability Components.pdf;/Users/julien/Zotero/storage/AS6KB22Y/1909.html}, google_scholar_id = {fFSKOagxvKUC}, }

NeurIPS Workshop

Objects of Violence: Synthetic Data for Practical ML in Human Rights Investigations

Lachlan Kermode, Jan Freyberg, Alican Akturk, Robert Trafford, Denis Kochetkov, Rafael Pardinas, Eyal Weizman, and Julien Cornebise

In NeurIPS 2019 Joint Workshop on AI for Social Good, 2019

arXiv Bib PDF

@inproceedings{kermode2019objects,
  title = {Objects of Violence: Synthetic Data for Practical {{ML}} in Human Rights Investigations},
  booktitle = {{{NeurIPS}} 2019 {{Joint Workshop}} on {{AI}} for {{Social Good}}},
  author = {Kermode, Lachlan and Freyberg, Jan and Akturk, Alican and Trafford, Robert and Kochetkov, Denis and Pardinas, Rafael and Weizman, Eyal and Cornebise, Julien},
  year = {2019},
  google_scholar_id = {r_AWSJRzSzQC},
  arxiv = {2004.01030},
}

NeurIPS Workshop

A Large-Scale Crowdsourced Analysis of Abuse against Women Journalists and Politicians on Twitter

Laure Delisle, Alfredo Kalaitzis, Krzysztof Majewski, Archy de Berker, Milena Marin, and Julien Cornebise

In NeurIPS 2019 Joint Workshop on AI for Social Good, 2019

arXiv Bib PDF

@inproceedings{delisle2019large,
  title = {A Large-Scale Crowdsourced Analysis of Abuse against Women Journalists and Politicians on {{Twitter}}},
  booktitle = {{{NeurIPS}} 2019 {{Joint Workshop}} on {{AI}} for {{Social Good}}},
  author = {Delisle, Laure and Kalaitzis, Alfredo and Majewski, Krzysztof and {de Berker}, Archy and Marin, Milena and Cornebise, Julien},
  year = {2019},
  google_scholar_id = {cWzG1nlazyYC},
  arxiv = {1902.03093},
}

Nature

A Clinically Applicable Approach to Continuous Prediction of Future Acute Kidney Injury

Nenad Tomašev, Xavier Glorot, Jack W. Rae, Michal Zielinski, Harry Askham, Andre Saraiva, Anne Mottram, Clemens Meyer, Suman Ravuri, Ivan Protsyuk, Alistair Connell, Cían O. Hughes, Alan Karthikesalingam, Julien Cornebise, Hugh Montgomery, Geraint Rees, Chris Laing, Clifton R. Baker, Kelly Peterson, Ruth Reeves, Demis Hassabis, Dominic King, Mustafa Suleyman, Trevor Back, Christopher Nielson, Joseph R. Ledsam, and Shakir Mohamed

Nature, 2019

DOI Bib PDF

@article{tomavsev2019clinically,
  title = {A Clinically Applicable Approach to Continuous Prediction of Future Acute Kidney Injury},
  author = {Toma{\v s}ev, Nenad and Glorot, Xavier and Rae, Jack W. and Zielinski, Michal and Askham, Harry and Saraiva, Andre and Mottram, Anne and Meyer, Clemens and Ravuri, Suman and Protsyuk, Ivan and Connell, Alistair and Hughes, C{\'i}an O. and Karthikesalingam, Alan and Cornebise, Julien and Montgomery, Hugh and Rees, Geraint and Laing, Chris and Baker, Clifton R. and Peterson, Kelly and Reeves, Ruth and Hassabis, Demis and King, Dominic and Suleyman, Mustafa and Back, Trevor and Nielson, Christopher and Ledsam, Joseph R. and Mohamed, Shakir},
  year = {2019},
  journal = {Nature},
  volume = {572},
  number = {7767},
  pages = {116--119},
  publisher = {Nature Publishing Group},
  google_scholar_id = {3htObqc8RwsC},
  doi = {10.1038/s41586-019-1390-1},
}

ICLR Workshop

Reproducibility and Stability Analysis in Metric-Based Few-Shot Learning.

Thomas Boquet, Laure Delisle, Denis Kochetkov, Nathan Schucher, Boris N. Oreshkin, and Julien Cornebise

In ICLR Workshop on Reproducibility in Machine Learning, 2019

Bib PDF

@inproceedings{boquet2019reproducibility,
  title = {Reproducibility and {{Stability Analysis}} in {{Metric-Based Few-Shot Learning}}.},
  author = {Boquet, Thomas and Delisle, Laure and Kochetkov, Denis and Schucher, Nathan and Oreshkin, Boris N. and Cornebise, Julien},
  year = {2019},
  booktitle = {{ICLR} Workshop on Reproducibility in Machine Learning},
  urldate = {2024-10-27},
  google_scholar_id = {2tRrZ1ZAMYUC}
}

ICLR Workshop

Planning with Latent Simulated Trajectories

Alexandre Piché, Valentin Thomas, Cyril Ibrahim, Julien Cornebise, and Chris Pal

In Proceedings of the Workshop on “Structure & Priors in Reinforcement Learning” at ICLR 2019, 2019

Bib PDF

@inproceedings{piche2019planning,
  title = {Planning with {{Latent Simulated Trajectories}}},
  booktitle = {Proceedings of the {{Workshop}} on ``{{Structure}} \& {{Priors}} in {{Reinforcement Learning}}'' at {{ICLR}} 2019},
  author = {Pich{\'e}, Alexandre and Thomas, Valentin and Ibrahim, Cyril and Cornebise, Julien and Pal, Chris},
  year = {2019},
  urldate = {2024-10-27},
  file = {/Users/julien/Zotero/storage/UEBA8L7E/Piché1 et al. - Planning with Latent Simulated Trajectories.pdf},
  google_scholar_id = {OR75R8vi5nAC},
}

2018

NeurIPS Workshop

Witnessing Atrocities: Quantifying Villages Destruction in Darfur with Crowdsourcing and Transfer Learning

Julien Cornebise, Daniel Worrall, Micah Farfour, and Milena Marin

In Proc. AI for Social Good NeurIPS2018 Workshop, NeurIPS’18, 2018

Bib PDF

@inproceedings{cornebise2018witnessing,
  title = {Witnessing Atrocities: Quantifying Villages Destruction in {{Darfur}} with Crowdsourcing and Transfer Learning},
  booktitle = {Proc. {{AI}} for Social Good {{NeurIPS2018}} Workshop, {{NeurIPS}}'18},
  author = {Cornebise, Julien and Worrall, Daniel and Farfour, Micah and Marin, Milena},
  year = {2018},
  google_scholar_id = {mNrWkgRL2YcC},
}

Nature Med

Clinically Applicable Deep Learning for Diagnosis and Referral in Retinal Disease

Jeffrey De Fauw, Joseph R. Ledsam, Bernardino Romera-Paredes, Stanislav Nikolov, Nenad Tomasev, Sam Blackwell, Harry Askham, Xavier Glorot, Brendan O’Donoghue, Daniel Visentin, George Van Den Driessche, Balaji Lakshminarayanan, Clemens Meyer, Faith Mackinder, Simon Bouton, Kareem Ayoub, Reena Chopra, Dominic King, Alan Karthikesalingam, Cían O. Hughes, Rosalind Raine, Julian Hughes, Dawn A. Sim, Catherine Egan, Adnan Tufail, Hugh Montgomery, Demis Hassabis, Geraint Rees, Trevor Back, Peng T. Khaw, Mustafa Suleyman, Julien Cornebise, Pearse A. Keane, and Olaf Ronneberger

Nature medicine, 2018

DOI Bib PDF

@article{defauw2018clinically,
  title = {Clinically Applicable Deep Learning for Diagnosis and Referral in Retinal Disease},
  author = {De Fauw, Jeffrey and Ledsam, Joseph R. and {Romera-Paredes}, Bernardino and Nikolov, Stanislav and Tomasev, Nenad and Blackwell, Sam and Askham, Harry and Glorot, Xavier and O'Donoghue, Brendan and Visentin, Daniel and Van Den Driessche, George and Lakshminarayanan, Balaji and Meyer, Clemens and Mackinder, Faith and Bouton, Simon and Ayoub, Kareem and Chopra, Reena and King, Dominic and Karthikesalingam, Alan and Hughes, C{\'i}an O. and Raine, Rosalind and Hughes, Julian and Sim, Dawn A. and Egan, Catherine and Tufail, Adnan and Montgomery, Hugh and Hassabis, Demis and Rees, Geraint and Back, Trevor and Khaw, Peng T. and Suleyman, Mustafa and Cornebise, Julien and Keane, Pearse A. and Ronneberger, Olaf},
  year = {2018},
  journal = {Nature medicine},
  volume = {24},
  number = {9},
  pages = {1342--1350},
  publisher = {Nature Publishing Group},
  google_scholar_id = {HIFyuExEbWQC},
  doi = {10.1038/s41591-018-0107-6},
}

Patent

Generalizable Medical Image Analysis Using Segmentation and Classification Neural Networks

Jeffrey De Fauw, Joseph R. Ledsam, Bernardino Romera-Paredes, Stanislav Nikolov, Nenad Tomasev, Samuel Blackwell, Harry Askham, Xavier Glorot, Balaji Lakshminarayanan, Trevor Back, Mustafa Suleyman, Pearse A. Keane, Olaf Ronneberger, and Julien Cornebise

2018

Bib HTML PDF

@patent{fauw_generalizable_2018,
  title = {Generalizable Medical Image Analysis Using Segmentation and Classification Neural Networks},
  author = {Fauw, Jeffrey De and Ledsam, Joseph R. and {Romera-Paredes}, Bernardino and Nikolov, Stanislav and Tomasev, Nenad and Blackwell, Samuel and Askham, Harry and Glorot, Xavier and Lakshminarayanan, Balaji and Back, Trevor and Suleyman, Mustafa and Keane, Pearse A. and Ronneberger, Olaf and Cornebise, Julien},
  year = {2018},
  number = {US11954902B2},
  urldate = {2024-10-27},
  assignee = {Google LLC},
  langid = {english},
  nationality = {US},
  keywords = {classification,image,input,neural networks,segmentation},
  file = {/Users/julien/Zotero/storage/IXN6PUX5/Fauw et al. - 2024 - Generalizable medical image analysis using segmentation and classification neural networks.pdf},
  google_scholar_id = {OP4eGU-M3BUC},
}

2017

F1000Research

Automated Analysis of Retinal Imaging Using Machine Learning Techniques for Computer Vision

Jeffrey De Fauw, Pearse Keane, Nenad Tomasev, Daniel Visentin, George Driessche, Mike Johnson, Cian O. Hughes, Carlton Chu, Joseph Ledsam, Trevor Back, Tunde Peto, Geraint Rees, Hugh Montgomery, Rosalind Raine, Olaf Ronneberger, and Julien Cornebise

F1000Research, 2017

Abs DOI Bib PDF

@article{faw2017automated,
  title = {Automated Analysis of Retinal Imaging Using Machine Learning Techniques for Computer Vision},
  author = {Fauw, Jeffrey De and Keane, Pearse and Tomasev, Nenad and Visentin, Daniel and van den Driessche, George and Johnson, Mike and Hughes, Cian O. and Chu, Carlton and Ledsam, Joseph and Back, Trevor and Peto, Tunde and Rees, Geraint and Montgomery, Hugh and Raine, Rosalind and Ronneberger, Olaf and Cornebise, Julien},
  year = {2017},
  journal = {F1000Research},
  volume = {5},
  pages = {1573},
  doi = {10.12688/f1000research.8996.2},
  urldate = {2024-10-27},
  langid = {english},
  pmid = {27830057},
  google_scholar_id = {XvxMoLDsR5gC},
  file = {/Users/julien/Zotero/storage/34X7IAVR/Fauw et al. - 2017 - Automated analysis of retinal imaging using machine learning techniques for computer vision.pdf}
}

2016

F1000Research

Applying Machine Learning to Automated Segmentation of Head and Neck Tumour Volumes and Organs at Risk on Radiotherapy Planning CT and MRI Scans

Carlton Chu, Jeffrey De Fauw, Nenad Tomasev, Bernardino Romera Paredes, Cían Hughes, Joseph Ledsam, Trevor Back, Hugh Montgomery, Geraint Rees, Rosalind Raine, Kevin Sullivan, Syed Moinuddin, Derek D’Souza, Olaf Ronneberger, Ruheena Mendes, and Julien Cornebise

F1000Research, 2016

DOI Bib PDF

@article{chu2016applying,
  title = {Applying Machine Learning to Automated Segmentation of Head and Neck Tumour Volumes and Organs at Risk on Radiotherapy Planning {{CT}} and {{MRI}} Scans},
  author = {Chu, Carlton and De Fauw, Jeffrey and Tomasev, Nenad and Paredes, Bernardino Romera and Hughes, C{\'i}an and Ledsam, Joseph and Back, Trevor and Montgomery, Hugh and Rees, Geraint and Raine, Rosalind and Sullivan, Kevin and Moinuddin, Syed and D'Souza, Derek and Ronneberger, Olaf and Mendes, Ruheena and Cornebise, Julien},
  year = {2016},
  journal = {F1000Research},
  volume = {5},
  pages = {2104},
  publisher = {F1000 Research Limited London, UK},
  urldate = {2024-10-27},
  doi = {10.12688/f1000research.9525.1},
  google_scholar_id = {umqufdRvDiIC},
}

Proceedings

Deep Learning and Data Labeling for Medical Applications: First International Workshop, LABELS 2016, and Second International Workshop, DLMIA 2016, Held in Conjunction with MICCAI 2016, Athens, Greece, October 21, 2016, Proceedings

Gustavo Carneiro, Diana Mateus, Loïc Peter, Andrew Bradley, João Manuel RS Tavares, Vasileios Belagiannis, João Paulo Papa, Jacinto C. Nascimento, Marco Loog, Zhi Lu, Jaime S Caroso, and Julien Cornebise

2016

DOI

2015

arXiv

Approximate Hubel-Wiesel Modules and the Data Structures of Neural Computation

Joel Z Leibo, Julien Cornebise, Sergio Gómez, and Demis Hassabis

arXiv preprint arXiv:1512.08457, 2015

arXiv Bib PDF

@article{leibo2015approximate,
  title = {Approximate {{Hubel-Wiesel}} Modules and the Data Structures of Neural Computation},
  author = {Leibo, Joel Z and Cornebise, Julien and G{\'o}mez, Sergio and Hassabis, Demis},
  year = {2015},
  journal = {arXiv preprint arXiv:1512.08457},
  arxiv = {1512.08457},
  google_scholar_id = {HtEfBTGE9r8C},
}

ICML

Weight Uncertainty in Neural Network

Charles Blundell, Julien Cornebise, Koray Kavukcuoglu, and Daan Wierstra

In International Conference on Machine Learning, 2015

Bib HTML PDF

@inproceedings{blundell2015weight,
  title = {Weight Uncertainty in Neural Network},
  booktitle = {International Conference on Machine Learning},
  author = {Blundell, Charles and Cornebise, Julien and Kavukcuoglu, Koray and Wierstra, Daan},
  year = {2015},
  pages = {1613--1622},
  publisher = {PMLR},
  google_scholar_id = {anf4URPfarAC},
}

2014

StatComp

Adaptive Sequential Monte Carlo by Means of Mixture of Experts

Julien Cornebise, Eric Moulines, and Jimmy Olsson

Statistics and Computing, 2014

DOI arXiv Bib PDF

@article{cornebise2014adaptive,
  title = {Adaptive Sequential {{Monte Carlo}} by Means of Mixture of Experts},
  author = {Cornebise, Julien and Moulines, Eric and Olsson, Jimmy},
  year = {2014},
  journal = {Statistics and Computing},
  volume = {24},
  pages = {317--337},
  publisher = {Springer US},
  google_scholar_id = {9yKSN-GCB0IC},
  arxiv = {1108.2836},
  doi = {10.1007/s11222-012-9372-2}
}

Book chapter

Chapter 12: Inference for Nonlinear State Space Models Particle

Randal Douc, Eric Moulines, and Julien Cornebise

In Nonlinear Time Series: Theory, Methods and Applications with R Examples, 2014

DOI Bib

@incollection{moulines2014inference,
  title = {Chapter 12: Inference for Nonlinear State Space Models Particle},
  booktitle = {Nonlinear Time Series: Theory, Methods and Applications with {{R}} Examples},
  author = {Douc, Randal and Moulines, Eric and Cornebise, Julien},
  year = {2014},
  publisher = {CRC Press},
  chapter = {12},
  doi = {10.1201/b16331}
}

Book chapter

Chapter 10: Particle Filtering

Randal Douc, Eric Moulines, and Julien Cornebise

In Nonlinear Time Series: Theory, Methods and Applications with R Examples, 2014

DOI Bib

@incollection{moulines2014particle,
  title = {Chapter 10: Particle Filtering},
  booktitle = {Nonlinear Time Series: Theory, Methods and Applications with {{R}} Examples},
  author = {Douc, Randal and Moulines, Eric and Cornebise, Julien},
  year = {2014},
  publisher = {CRC Press},
  chapter = {10},
  doi = {10.1201/b16331}
}

Book chapter

Chapter 11: Particle Smoothing

Randal Douc, Eric Moulines, and Julien Cornebise

In Nonlinear Time Series: Theory, Methods and Applications with R Examples, 2014

DOI Bib

@incollection{moulines2014particle_smoothing,
  title = {Chapter 11: Particle Smoothing},
  booktitle = {Nonlinear Time Series: Theory, Methods and Applications with {{R}} Examples},
  author = {Douc, Randal and Moulines, Eric and Cornebise, Julien},
  year = {2014},
  publisher = {CRC Press},
  chapter = {11},
  doi = {10.1201/b16331}
}

Patent

Recommending Content Using Neural Networks

Charles Blundell, and Julien Cornebise

2014

Bib HTML PDF

@patent{blundell_recommending_2014,
  title = {Recommending Content Using Neural Networks},
  author = {Blundell, Charles and Cornebise, Julien},
  year = {2014},
  number = {US11562209B1},
  urldate = {2024-10-27},
  assignee = {DeepMind Technologies Ltd},
  nationality = {US},
  keywords = {action,neural network,parameter,parameters,training},
  file = {/Users/julien/Zotero/storage/N4HQEW36/BLUNDELL and Cornebise - 2023 - Recommending content using neural networks.pdf},
}

2013

StatMed

Adaptive Markov Chain Monte Carlo Forward Projection for Statistical Analysis in Epidemic Modelling of Human Papillomavirus

Igor A Korostil, Gareth W Peters, Julien Cornebise, and David G Regan

Statistics in medicine, 2013

DOI Bib PDF

@article{korostil2013adaptive,
  title = {Adaptive {{Markov}} Chain {{Monte Carlo}} Forward Projection for Statistical Analysis in Epidemic Modelling of Human Papillomavirus},
  author = {Korostil, Igor A and Peters, Gareth W and Cornebise, Julien and Regan, David G},
  year = {2013},
  journal = {Statistics in medicine},
  volume = {32},
  number = {11},
  pages = {1917--1953},
  publisher = {Wiley},
  google_scholar_id = {WF5omc3nYNoC},
  doi = {10.1002/sim.5590},
}

Patent

Signal Processing Systems

Julien Cornebise, Danilo Jimenez Rezende, and Daniël Pieter Wierstra

2013

Bib HTML PDF

@patent{cornebise_signal_2013,
  title = {Signal Processing Systems},
  author = {Cornebise, Julien and Rezende, Danilo Jimenez and Wierstra, Dani{\"e}l Pieter},
  year = {2013},
  number = {EP2973241B1},
  urldate = {2024-10-27},
  assignee = {DeepMind Technologies Ltd},
  langid = {english},
  nationality = {EP},
  keywords = {category,probability,processing system,signal processing,vector},
  file = {/Users/julien/Zotero/storage/H3PL5I8K/CORNEBISE et al. - 2020 - Signal processing systems.pdf},
  google_scholar_id = {0izLItjtcgwC},
}

2012

JRSSB Comment

Some Discussions of D. Fearnhead and D. Prangle’s Read Paper “Constructing Summary Statistics for Approximate Bayesian Computation: Semi-Automatic Approximate Bayesian Computation”

Christophe Andrieu, Simon Barthelmé, Nicolas Chopin, Julien Cornebise, Arnaud Doucet, Mark Girolami, Ioannis Kosmidis, Ajay Jasra, Anthony Lee, Jean-Michel Marin, Pierre Pudlo, Christian P. Robert, Mohammed Sedki, and Sumeetpal S. Singh

Journal of the Royal Statistical Society: Series B, 2012

arXiv Bib PDF

@article{andrieu2012some,
  title = {Some Discussions of {{D}}. {{Fearnhead}} and {{D}}. {{Prangle}}'s {{Read Paper}} ``{{Constructing}} Summary Statistics for Approximate {{Bayesian}} Computation: Semi-Automatic Approximate {{Bayesian}} Computation''},
  author = {Andrieu, Christophe and Barthelm{\'e}, Simon and Chopin, Nicolas and Cornebise, Julien and Doucet, Arnaud and Girolami, Mark and Kosmidis, Ioannis and Jasra, Ajay and Lee, Anthony and Marin, Jean-Michel and Pudlo, Pierre and Robert, Christian P. and Sedki, Mohammed and Singh, Sumeetpal S.},
  year = {2012},
  journal = {Journal of the Royal Statistical Society: Series B},
  arxiv = {1201.1314},
}

2011

JRSSB Comment

RMHMC for unidentifiable models: Discussion on “Riemann Manifold Langevin and Hamiltonian Monte Carlo Methods” by M. Girolami and B. Calderhead

Luke Bornn, and Julien Cornebise

Journal of the Royal Statistical Society: Series B, 2011

arXiv Bib PDF

@article{bornn2011discussion,
  title = {RMHMC for unidentifiable models: Discussion on ``{{Riemann}} Manifold {{Langevin}} and {{Hamiltonian Monte Carlo}} Methods'' by {{M}}. {{Girolami}} and {{B}}. {{Calderhead}}},
  author = {Bornn, Luke and Cornebise, Julien},
  year = {2011},
  journal = {Journal of the Royal Statistical Society: Series B},
  volume = {73},
  number = {2},
  pages = {174--177},
  arxiv = {1011.0057},
}

JRSSB Comment

On Adaptive Monte Carlo: Discussion on “Riemann Manifold Langevin and Hamiltonian Monte Carlo Methods” by M. Girolami and B. Calderhead

Julien Cornebise, and Gareth W Peters

Journal of the Royal Statistical Society: Series B, 2011

arXiv Bib PDF

@article{cornebise2011discussion,
  title = {On Adaptive Monte Carlo: Discussion on ``{{Riemann}} Manifold {{Langevin}} and {{Hamiltonian Monte Carlo}} Methods'' by {{M}}. {{Girolami}} and {{B}}. {{Calderhead}}},
  author = {Cornebise, Julien and Peters, Gareth W},
  year = {2011},
  journal = {Journal of the Royal Statistical Society: Series B},
  volume = {73},
  number = {2},
  pages = {179},
  arxiv = {1011.0057},
}

SAGMB

On Optimality of Kernels for Approximate Bayesian Computation Using Sequential Monte Carlo

Sarah Filippi, Chris P. Barnes, Julien Cornebise, and Michael P.H. Stumpf

Statistical Applications in Genetics and Molecular Biology, 2011

DOI Bib PDF

@article{filippi2011optimality,
  title = {On Optimality of Kernels for Approximate {{Bayesian}} Computation Using Sequential {{Monte Carlo}}},
  author = {Filippi, Sarah and Barnes, Chris P. and Cornebise, Julien and Stumpf, Michael P.H.},
  year = {2011},
  journal = {Statistical Applications in Genetics and Molecular Biology},
  volume = {12},
  number = {1},
  pages = {87--107},
  google_scholar_id = {YsMSGLbcyi4C},
  doi = {10.1515/sagmb-2012-0069},
}

SSP

A Comparative Study of Monte-Carlo Methods for Multitarget Tracking

François Septier, Julien Cornebise, Simon Godsill, and Yves Delignon

In 2011 IEEE Statistical Signal Processing Workshop (SSP), 2011

DOI Bib PDF

@inproceedings{septier2011comparative,
  title = {A Comparative Study of {{Monte-Carlo}} Methods for Multitarget Tracking},
  booktitle = {2011 {{IEEE}} Statistical Signal Processing Workshop ({{SSP}})},
  author = {Septier, Fran{\c c}ois and Cornebise, Julien and Godsill, Simon and Delignon, Yves},
  year = {2011},
  pages = {205--208},
  publisher = {IEEE},
  google_scholar_id = {qjMakFHDy7sC},
  doi = {10.1109/SSP.2011.5967660},
}

2010

JRSSB Comment

Discussion on the Paper by Andrieu, Doucet, and Holenstein

Julien Cornebise, and Gareth W Peters

Journal of the Royal Statistical Society: Series B, 2010

arXiv Bib PDF

@article{cornebise2010Comment,
  title = {Discussion on the Paper by {{Andrieu}}, {{Doucet}}, and {{Holenstein}}},
  author = {Cornebise, Julien and Peters, Gareth W},
  year = {2010},
  journal = {Journal of the Royal Statistical Society: Series B},
  volume = {72},
  number = {3},
  pages = {317--319},
  arxiv = {0911.3866},
}

NeurIPS Workshop

Field Report: Adaptive Particle MCMC for Mixed Effect Models and Stochastic Differential Equations

Julien Cornebise, Gareth W Peters, and Arnaud Doucet

In NIPS 2010 Workshop on Monte Carlo Methods, 2010

Bib

@inproceedings{cornebise2010field,
  title = {Field {{Report}}: {{Adaptive Particle MCMC}} for {{Mixed Effect Models}} and {{Stochastic Differential Equations}}},
  booktitle = {{{NIPS}} 2010 {{Workshop}} on {{Monte Carlo Methods}}},
  author = {Cornebise, Julien and Peters, Gareth W and Doucet, Arnaud},
  year = {2010},
  address = {Whistler, BC, Canada},
  howpublished = {NIPS 2010 Workshop Monte Carlo Methods}
}

JRSSB Comment

Discussion on the Paper by Andrieu, Doucet, and Holenstein

Gareth W Peters, and Julien Cornebise

Journal of the Royal Statistical Society: Series B, 2010

arXiv Bib PDF

@article{peters2010discussion,
  title = {Discussion on the Paper by {{Andrieu}}, {{Doucet}}, and {{Holenstein}}},
  author = {Peters, Gareth W and Cornebise, Julien},
  year = {2010},
  journal = {Journal of the Royal Statistical Society: Series B},
  volume = {72},
  number = {3},
  pages = {329--330},
  arxiv = {0911.3866},
}

2009

PhD Manuscript

Méthodes de Monte Carlo Séquentielles Adaptatives

Julien Cornebise

Université Pierre et Marie Curie, 2009

Savage Award Bib PDF

This PhD received the Savage Award in Theory and Methods for 2010 from the International Society for Bayesian Analysis.

@phdthesis{cornebise2009methodes,
  title = {M{\'e}thodes de {{Monte Carlo}} S{\'e}quentielles Adaptatives},
  author = {Cornebise, Julien},
  year = {2009},
  school = {Universit{\'e} Pierre et Marie Curie},
  google_scholar_id = {ufrVoPGSRksC},
}

2008

StatComp

Adaptive Methods for Sequential Importance Sampling with Application to State Space Models

Julien Cornebise, Éric Moulines, and Jimmy Olsson

Statistics and Computing, 2008

DOI arXiv Bib PDF

@article{cornebise2008adaptive,
  title = {Adaptive Methods for Sequential Importance Sampling with Application to State Space Models},
  author = {Cornebise, Julien and Moulines, {\'E}ric and Olsson, Jimmy},
  year = {2008},
  journal = {Statistics and Computing},
  volume = {18},
  pages = {461--480},
  publisher = {Springer US},
  google_scholar_id = {u5HHmVD_uO8C},
  doi = {10.1007/s11222-008-9089-4},
  arxiv = {0803.0054},
}

EUSIPCO

Adaptive Methods for Sequential Importance Sampling with Application to State Space Models

Julien Cornebise, Eric Moulines, and Jimmy Olsson

In 16th European Signal Processing Conference (EUSIPCO 2008), 2008

Finalist for Best Student Paper Award Bib

Finalist for Best Student Paper Award

@inproceedings{cornebise2008adaptive_eusipco,
  title = {Adaptive Methods for Sequential Importance Sampling with Application to State Space Models},
  booktitle = {16th European Signal Processing Conference ({{EUSIPCO}} 2008)},
  author = {Cornebise, Julien and Moulines, Eric and Olsson, Jimmy},
  year = {2008},
  address = {Lausanne, Switzerland}
}

2006

SFDS

Planification d’expérience Optimale et Équations Différentielles : Révision Des Bases et Méthodologie

Julien Cornebise, and Bruno Boulanger

In Actes Des 38èmes Journées de Statistique de La SFDS, 2006

Bib PDF

@inproceedings{cornebise2006planification,
  title = {Planification d'exp{\'e}rience Optimale et {\'E}quations Diff{\'e}rentielles : R{\'e}vision Des Bases et M{\'e}thodologie},
  booktitle = {Actes Des 38{\`e}mes {{Journ{\'e}es}} de {{Statistique}} de La {{SFDS}}},
  author = {Cornebise, Julien and Boulanger, Bruno},
  year = {2006},
  address = {Clamart, France},
  google_scholar_id = {zYLM7Y9cAGgC}
}

2005

IGARSS

A Meteosat Second Generation Receiving, Processing and Storing Images System Developed by Engineer Students

Laurent Beaudoin, Louis-Aurélien Charbardès, Julien Cornebise, Christophe Dufour, Konrad Florczak, François Gachot, and Pierre Schott

In IGARSS, 2005

DOI Bib PDF

@inproceedings{beaudoin2005meteosat,
  title = {A {{Meteosat}} Second Generation Receiving, Processing and Storing Images System Developed by Engineer Students},
  booktitle = {{{IGARSS}}},
  author = {Beaudoin, Laurent and Charbard{\`e}s, Louis-Aur{\'e}lien and Cornebise, Julien and Dufour, Christophe and Florczak, Konrad and Gachot, Fran{\c c}ois and Schott, Pierre},
  year = {2005},
  pages = {3159--3162},
  google_scholar_id = {d1gkVwhDpl0C},
  doi = {10.1109/IGARSS.2005.1526510},
}

ASMDA

A Practical Implementation of the Gibbs Sampler for Mixture of Distributions: Application to the Determination of Specifications in Food Industry

Julien Cornebise, Myriam Maumy, and Philippe Girard

In International Symposium on Applied Stochastic Models and Data Analysis, 2005

Bib HTML PDF

@inproceedings{cornebise2005practical,
  title = {A Practical Implementation of the {{Gibbs}} Sampler for Mixture of Distributions: {{Application}} to the Determination of Specifications in Food Industry},
  booktitle = {International Symposium on Applied Stochastic Models and Data Analysis},
  author = {Cornebise, Julien and Maumy, Myriam and Girard, Philippe},
  year = {2005},
  pages = {828--838},
  publisher = {ASMDA},
  google_scholar_id = {u-x6o8ySG0sC}
}