Mario Lučić
- Computer Vision and Pattern Recognition top 2%
- Artificial Intelligence top 5%
- Signal Processing top 10%
- Computer Graphics and Computer-Aided Design top 5%
- Computational Mechanics
- Co-authors
- Olivier BachemAndreas KrauseNeil HoulsbyXiaohua ZhaiMarvin RitterTing ChenSylvain GellyS. Hamed Hassani
- Topics
- Generative Adversarial Networks and Image Synthesis (6 papers)Machine Learning and Algorithms (6 papers)Data Management and Algorithms (5 papers)
- Cited by
- Computer Vision and Pattern RecognitionComputer Graphics and Computer-Aided DesignArtificial Intelligence
- Journals
- ACM Transactions on GraphicsJournal of Machine Learning Research2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
- Partner nations
- United StatesSwitzerlandGermany
In The Last Decade
Mario Lučić
30 papers receiving 679 citations
Peers
Comparison fields: 5 of 83
- Computer Vision and Pattern Recognition 436
- Artificial Intelligence 350
- Signal Processing 98
- Computer Graphics and Computer-Aided Design 63
- Computational Mechanics 62
Countries citing papers authored by Mario Lučić
This map shows the geographic impact of Mario Lučić'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 Mario Lučić with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mario Lučić more than expected).
Fields of papers citing papers by Mario Lučić
This network shows the impact of papers produced by Mario Lučić. 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 Mario Lučić. The network helps show where Mario Lučić may publish in the future.
Co-authorship network of co-authors of Mario Lučić
This figure shows the co-authorship network connecting the top 25 collaborators of Mario Lučić. A scholar is included among the top collaborators of Mario Lučić 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 Mario Lučić. Mario Lučić is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 5 | |
| 2 | 20 | |
| 3 | 21 | |
| 4 | 6 | |
| 5 | On Mutual Information Maximization for Representation Learning | 15 |
| 6 | 2 | |
| 7 | Evaluating Generative Models using Divergence Frontiers | 1 |
| 8 | High-Fidelity Image Generation With Fewer Labels | 16 |
| 9 | The Visual Task Adaptation Benchmark | 22 |
| 10 | 182 | |
| 11 | On Self Modulation for Generative Adversarial Networks | 14 |
| 12 | One-shot Coresets: The Case of k-Clustering | 6 |
| 13 | 52 | |
| 14 | 15 | |
| 15 | Distributed and Provably Good Seedings for k-Means in Constant Rounds | 8 |
| 16 | Uniform Deviation Bounds for k-Means Clustering | 6 |
| 17 | Training Mixture Models at Scale via Coresets | 8 |
| 18 | Fast and Provably Good Seedings for k-Means | 46 |
| 19 | 78 | |
| 20 | Linear-time outlier detection via sensitivity | 1 |
About Mario Lučić
Mario Lučić is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Artificial Intelligence, having authored 30 papers that have together received 710 indexed citations. Recurring topics across this work include Generative Adversarial Networks and Image Synthesis (6 papers), Machine Learning and Algorithms (6 papers) and Data Management and Algorithms (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (436 citations), Computer Graphics and Computer-Aided Design (63 citations) and Artificial Intelligence (350 citations). Mario Lučić has collaborated with scholars based in United States, Switzerland and Germany. Frequent co-authors include Olivier Bachem, Andreas Krause, Neil Houlsby, Xiaohua Zhai, Marvin Ritter, Ting Chen, Sylvain Gelly, S. Hamed Hassani, Mehdi S. M. Sajjadi and Olivier Bousquet. Their work appears in journals such as ACM Transactions on Graphics, Journal of Machine Learning Research and 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
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.