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.
Extracting and composing robust features with denoising autoencoders
20084.4k citationsPascal Vincent, Hugo Larochelle et al.profile →
Stacked Denoising Autoencoders: Learning Useful Representations in a Deep Network with a Local Denoising Criterion
20103.3k citationsPascal Vincent, Hugo Larochelle et al.Journal of Machine Learning Researchprofile →
Countries citing papers authored by Pierre-Antoine Manzagol
Since Specialization
Citations
This map shows the geographic impact of Pierre-Antoine Manzagol'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 Pierre-Antoine Manzagol with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pierre-Antoine Manzagol more than expected).
Fields of papers citing papers by Pierre-Antoine Manzagol
This network shows the impact of papers produced by Pierre-Antoine Manzagol. 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 Pierre-Antoine Manzagol. The network helps show where Pierre-Antoine Manzagol may publish in the future.
Co-authorship network of co-authors of Pierre-Antoine Manzagol
This figure shows the co-authorship network connecting the top 25 collaborators of Pierre-Antoine Manzagol.
A scholar is included among the top collaborators of Pierre-Antoine Manzagol 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 Pierre-Antoine Manzagol. Pierre-Antoine Manzagol is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Pierre-Antoine Manzagol is a scholar working on Signal Processing, Software and Artificial Intelligence, having authored 9 papers that have together received 8.1k indexed citations. Recurring topics across this work include Generative Adversarial Networks and Image Synthesis (3 papers), Blind Source Separation Techniques (2 papers) and Sparse and Compressive Sensing Techniques (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (3.1k citations), Artificial Intelligence (3.7k citations) and Signal Processing (1.2k citations). Pierre-Antoine Manzagol has collaborated with scholars based in Canada, United States and Sweden. Frequent co-authors include Yoshua Bengio, Pascal Vincent, Hugo Larochelle, Dumitru Erhan, Samy Bengio, Nicolas Le Roux, Thierry Bertin-Mahieux, Douglas Eck, Pascal Lamblin and Subhodeep Moitra. Their work appears in journals such as Journal of Machine Learning Research, arXiv (Cornell University) and Neural Information Processing Systems.
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.