Lucas Caccia

458 total citations
4 papers, 46 citations indexed

About

Lucas Caccia is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Radiological and Ultrasound Technology. According to data from OpenAlex, Lucas Caccia has authored 4 papers receiving a total of 46 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Artificial Intelligence, 2 papers in Computer Vision and Pattern Recognition and 1 paper in Radiological and Ultrasound Technology. Recurrent topics in Lucas Caccia's work include Sparse and Compressive Sensing Techniques (1 paper), Multimodal Machine Learning Applications (1 paper) and Seismology and Earthquake Studies (1 paper). Lucas Caccia is often cited by papers focused on Sparse and Compressive Sensing Techniques (1 paper), Multimodal Machine Learning Applications (1 paper) and Seismology and Earthquake Studies (1 paper). Lucas Caccia collaborates with scholars based in Canada, Italy and Israel. Lucas Caccia's co-authors include Joëlle Pineau, M. Caccia, William Fedus, Hugo Larochelle, Laurent Charlin, Eugene Belilovsky, M. Martini, Massimo Zucchetti and Massimo Caccia and has published in prestigious journals such as arXiv (Cornell University) and International Conference on Learning Representations.

In The Last Decade

Lucas Caccia

3 papers receiving 45 citations

Peers

Countries citing papers authored by Lucas Caccia

Since Specialization

Citations

This map shows the geographic impact of Lucas Caccia'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 Lucas Caccia with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lucas Caccia more than expected).

Fields of papers citing papers by Lucas Caccia

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Lucas Caccia. 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 Lucas Caccia. The network helps show where Lucas Caccia may publish in the future.

Co-authorship network of co-authors of Lucas Caccia

This figure shows the co-authorship network connecting the top 25 collaborators of Lucas Caccia. A scholar is included among the top collaborators of Lucas Caccia 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 Lucas Caccia. Lucas Caccia is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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4 of 4 papers shown

#	Work	Indexed citations
1	Language GANs Falling Short 2020 ·International Conference on Learning Representations ·M. Caccia, Lucas Caccia, William Fedus, Hugo Larochelle, Joëlle Pineau, Laurent Charlin	34
2	Online Learned Continual Compression with Stacked Quantization Module. 2019 ·arXiv (Cornell University) ·Lucas Caccia, Eugene Belilovsky, Massimo Caccia, Joëlle Pineau	1
3	Online Learned Continual Compression with Adaptive Quantization Modules 2019 ·arXiv (Cornell University) ·Lucas Caccia, Eugene Belilovsky, M. Caccia, Joëlle Pineau	11
4	THE TELLUS PROJECT, A STUDY OF SEISMIC PRECURSORS 2015 ·(unknown), (unknown), Lucas Caccia, (unknown), (unknown), (unknown), M. Martini, (unknown), Massimo Zucchetti	0

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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