Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
A blind source separation technique using second-order statistics
2005850 citationsOlivier Cappé, Éric Moulines et al.Digital Access to Libraries (Université catholique de Louvain (UCL), l'Université de Namur (UNamur) and the Université Saint-Louis (USL-B))profile →
Pitch-synchronous waveform processing techniques for text-to-speech synthesis using diphones
This map shows the geographic impact of Éric Moulines'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 Éric Moulines with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Éric Moulines more than expected).
This network shows the impact of papers produced by Éric Moulines. 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 Éric Moulines. The network helps show where Éric Moulines may publish in the future.
Co-authorship network of co-authors of Éric Moulines
This figure shows the co-authorship network connecting the top 25 collaborators of Éric Moulines.
A scholar is included among the top collaborators of Éric Moulines based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Éric Moulines. Éric Moulines is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Dieuleveut, Aymeric, et al.. (2021). Federated-EM with heterogeneity mitigation and variance reduction. Neural Information Processing Systems. 34.3 indexed citations
6.
Lerasle, Matthieu, et al.. (2019). Estimation de densité pour la MAMA. HAL (Le Centre pour la Communication Scientifique Directe).1 indexed citations
7.
Miasojedow, Błażej, et al.. (2019). Non-asymptotic Analysis of Biased Stochastic Approximation Scheme.. HAL (Le Centre pour la Communication Scientifique Directe). 1944–1974.2 indexed citations
8.
Wai, Hoi-To, et al.. (2016). Decentralized Projection-free Optimization for Convex and Non-convex Problems.. arXiv (Cornell University).1 indexed citations
Fort, Gersende, et al.. (2014). Convergence of Markovian Stochastic Approximation with discontinuous dynamics.7 indexed citations
11.
Sayrac, Berna, et al.. (2014). Centralized self-optimization of eICIC with varying traffic in LTE-A. European Wireless Conference. 1–6.1 indexed citations
12.
Douc, Randal, Éric Moulines, & David S. Stoffer. (2014). Nonlinear time series: theory, methods and applications with R examples. SPIRE - Sciences Po Institutional REpository.44 indexed citations
13.
Sayrac, Berna, et al.. (2014). Centralized Self-Optimization Performance of eICIC and AAS in LTE-A: A Comparison. European Wireless Conference. 1–6.1 indexed citations
14.
Douc, Randal, Éric Moulines, & Jimmy Olsson. (2013). Long-term stability of sequential Monte Carlo methods under verifiable conditions.23 indexed citations
Fort, Gersende, Sean Meyn, Éric Moulines, & Pierre Priouret. (2006). ODE methods for skip-free Markov chain stability with applications to MCMC. arXiv (Cornell University).5 indexed citations
19.
Olsson, Jimmy, Olivier Cappé, Randal Douc, & Éric Moulines. (2006). Sequential Monte Carlo smoothing with estimation in non-linear state space models. Lund University Publications (Lund University).2 indexed citations
20.
Cappé, Olivier, et al.. (2005). 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)).850 indexed citations breakdown →
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.