Olivier Cappé

10.0k citations

69 papers · 5.2k indexed · 4 hit papers · h-index 28

Impact in

Signal Processing top 0.2%
- Speech and Audio Processing
- Music and Audio Processing
Artificial Intelligence top 0.2%
- Target Tracking and Data Fusion in Sensor Networks
- Speech Recognition and Synthesis
- Bayesian Methods and Mixture Models
- Gaussian Processes and Bayesian Inference

Papers in

Signal Processing 30
- Speech and Audio Processing 22
- Blind Source Separation Techniques 12
- Music and Audio Processing 8
Statistics and Probability 12
- Markov Chains and Monte Carlo Methods 8

Co-authors: Éric Moulines Randal Douc Yannis Stylianou Simon Godsill François Yvon Christian P. Robert Jean‐Michel Marin Thomas Lavergne
Journals: IEEE Transactions on Speech and Audio Processing (5 papers)IEEE Transactions on Signal Processing (4 papers)IEEE Journal of Selected Topics in Signal Processing (2 papers)Journal of the American Statistical Association (2 papers)Journal of Computational and Graphical Statistics (2 papers)
Partner nations: France United Kingdom United States

In The Last Decade

Olivier Cappé

64 papers receiving 4.8k citations

Hit Papers

align trajectories log scale

An Overview of Existing Methods and Recent Advances in Sequential Monte Carlo 2007 · 649 citations

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if any of the following hold:

it has ≥500 total citations;
it reaches ≥1.5× the top-1% citation threshold for papers in the same subfield and year (the threshold is the minimum needed to enter the top 1%, not the average within it);
it reaches the top citation threshold in at least one of its specific research topics.

2007 Proceedings of the IEEE
2005 Comparison of resampling schemes for particle filtering
2005 Digital Access to Libraries (Université catholique de Louvain (UCL), l'Université de Namur (UNamur) and the Université Saint-Louis (USL-B))
1998 IEEE Transactions on Speech and Audio Processing

Peers

Countries citing papers authored by Olivier Cappé

Since Specialization

Citations

This map shows the geographic impact of Olivier Cappé's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Olivier Cappé with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Olivier Cappé more than expected).

Fields of papers citing papers by Olivier Cappé

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Olivier Cappé. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Olivier Cappé. The network helps show where Olivier Cappé may publish in the future.

Co-authors

The 25 scholars most cited alongside Olivier Cappé, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Olivier Cappé Line = papers co-authored together Olivier Cappé links everyone, so they are left out of the graph.

All Works

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20 of 20 papers shown

#	Work
1	Adaptive Metropolis with Online Relabeling SPIRE - Sciences Po Institutional REpository ·A Ikhwana, Olivier Cappé, Gersende Fort, Balázs Kégl	2012	0
2	Parametric Bandits: The Generalized Linear Case Neural Information Processing Systems ·Sarah Filippi, Olivier Cappé, Aurélien Garivier, Csaba Szepesvári	2010	105
3	Practical Very Large Scale CRFs Thomas Lavergne, Olivier Cappé, François Yvon	2010	153
4	On-Line Expectation–Maximization Algorithm for latent Data Models Journal of the Royal Statistical Society Series B (Statistical Methodology) ·Olivier Cappé, Éric Moulines	2009	285
5	Estimation of cosmological parameters using adaptive importance sampling Physical review. D. Particles, fields, gravitation, and cosmology ·Darren Wraith, M. Kilbinger, K. Benabed, Olivier Cappé, J.-F. Cardoso, Gersende Fort, S. Prunet, Christian P. Robert	2009	39
6	Sequential Monte Carlo smoothing with application to parameter estimation in nonlinear state space models Bernoulli ·Jimmy Olsson, Olivier Cappé, Randal Douc, Éric Moulines	2008	82
7	Using LDA to detect semantically incoherent documents Hemant Misra, Olivier Cappé, François Yvon	2008	34
8	An Overview of Existing Methods and Recent Advances in Sequential Monte Carlo Proceedings of the IEEE ·Olivier Cappé, Simon Godsill, Éric Moulines Hit paper breakdown →	2007	649
9	Sequential Monte Carlo smoothing with estimation in non-linear state space models Lund University Publications (Lund University) ·Jimmy Olsson, Olivier Cappé, Randal Douc, Éric Moulines	2006	2
10	Recursive Em Algorithm with Applications to Doa Estimation Olivier Cappé, Mariam Shahid Noorani, Éric Moulines	2006	9
11	Inference in Hidden Markov Models Digital Access to Libraries (Université catholique de Louvain (UCL), l'Université de Namur (UNamur) and the Université Saint-Louis (USL-B)) ·Olivier Cappé, (unknown), Éric Moulines Hit paper breakdown →	2005	850
12	Inference in Hidden Markov Models (Springer Series in Statistics) Olivier Cappé, Éric Moulines, Tobias Rydén	2005	156
13	Comparison of resampling schemes for particle filtering Randal Douc, Olivier Cappé Hit paper breakdown →	2005	533
14	Recursive computation of the score and observed information matrix in hidden markov models Olivier Cappé, Éric Moulines	2005	8
15	Population Monte Carlo for Ion Channel Restoration Base Institutionnelle de Recherche de l'université Paris-Dauphine (BIRD) (University Paris-Dauphine) ·Olivier Cappé, Juan Yang, Jean‐Michel Marin, Christian P. Robert	2004	5
16	Le modèle "monomaniaque" un modèle statistique simple pour l'analyse exploratoire d'un corpus de textes HAL (Le Centre pour la Communication Scientifique Directe) ·Fabrice Clérot, Olivier Collin, Olivier Cappé, Éric Moulines	2004	1
17	Semi-blind subspace techniques for digital communication systems A. Heidenblut, Éric Moulines, Olivier Cappé, A. Gorokhov	2003	0
18	Simulation-based methods for blind maximum-likelihood filter identification Signal Processing ·Olivier Cappé, Randal Douc, Marc Lavielle, Éric Moulines	1999	21
19	An algorithm for maximum likelihood estimation of hidden Markov models with unknown state-tying IEEE Transactions on Speech and Audio Processing ·Olivier Cappé, Frank Hecker, Denis Jouvet, Éric Moulines	1998	9
20	Statistical methods for voice quality transformation Yannis Stylianou, Olivier Cappé, Éric Moulines	1995	64

About Olivier Cappé

Olivier Cappé is a scholar working on Signal Processing, Statistics and Probability, Artificial Intelligence, Computer Vision and Pattern Recognition and Computational Mechanics, having authored 69 papers that have together received 5.2k indexed citations. Recurring topics across this work include Speech and Audio Processing (22 papers), Bayesian Methods and Mixture Models (18 papers), Blind Source Separation Techniques (12 papers), Music and Audio Processing (8 papers), Target Tracking and Data Fusion in Sensor Networks (8 papers), Markov Chains and Monte Carlo Methods (8 papers), Advanced Adaptive Filtering Techniques (7 papers) and Image and Signal Denoising Methods (7 papers). The work is most often cited by research in Signal Processing (1.6k citations), Artificial Intelligence (3.1k citations), Statistics and Probability (731 citations), Computer Vision and Pattern Recognition (519 citations) and Computational Mathematics (14 citations). Olivier Cappé has collaborated with scholars based in France, United Kingdom and United States. Frequent co-authors include Éric Moulines, Randal Douc, Yannis Stylianou, Simon Godsill, François Yvon, Christian P. Robert, Jean‐Michel Marin, Thomas Lavergne, Tobias Rydén and Hemant Misra. Their work appears in journals such as IEEE Transactions on Speech and Audio Processing, IEEE Transactions on Signal Processing, IEEE Journal of Selected Topics in Signal Processing, Journal of the American Statistical Association and Journal of Computational and Graphical Statistics.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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