Löıc Matthey
Impact in
-
- Generative Adversarial Networks and Image Synthesis
- Multimodal Machine Learning Applications
- Human Pose and Action Recognition
- Artificial Intelligence top 2%
- Domain Adaptation and Few-Shot Learning
- Topic Modeling
- Anomaly Detection Techniques and Applications
- Adversarial Robustness in Machine Learning
Papers in
-
- Domain Adaptation and Few-Shot Learning 4
- Machine Learning and Data Classification 2
-
- Generative Adversarial Networks and Image Synthesis 2
- Co-authors
- Alexander LerchnerChristopher BurgessIrina HigginsMatthew BotvinickArka PalXavier GlorotShakir MohamedPaul M. Bays
- Journals
- PLoS Computational Biology (1 paper)Adaptive Agents and Multi-Agents Systems (1 paper)arXiv (Cornell University) (3 papers)International Conference on Learning Representations (2 papers)Neural Information Processing Systems (1 paper)
- Partner nations
- United StatesUnited KingdomSwitzerland
In The Last Decade
Löıc Matthey
11 papers receiving 1.3k citations
Hit Papers
Peers
Comparison fields: 5 of 117
- Computer Vision and Pattern Recognition 613
- Artificial Intelligence 706
- Signal Processing 144
- Computer Graphics and Computer-Aided Design 26
- Cognitive Neuroscience 108
Countries citing papers authored by Löıc Matthey
This map shows the geographic impact of Löıc Matthey'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 Löıc Matthey with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Löıc Matthey more than expected).
Fields of papers citing papers by Löıc Matthey
This network shows the impact of papers produced by Löıc Matthey. 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 Löıc Matthey. The network helps show where Löıc Matthey may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Löıc Matthey, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 5 | |
| 2 | 2021 | 4 | |
| 3 | Unsupervised Model Selection for Variational Disentangled Representation Learning | 2020 | 5 |
| 4 | A Heuristic for Unsupervised Model Selection for Variational Disentangled Representation Learning. | 2019 | 1 |
| 5 | Multi-Object Representation Learning with Iterative Variational Inference | 2019 | 13 |
| 6 | SCAN: Learning Hierarchical Compositional Visual Concepts | 2018 | 17 |
| 7 | Life-Long Disentangled Representation Learning with Cross-Domain Latent Homologies | 2018 | 18 |
| 8 | beta-VAE: Learning Basic Visual Concepts with a Constrained Variational Framework Hit paper breakdown → | 2017 | 1198 |
| 9 | 2015 | 38 | |
| 10 | 2010 | 8 | |
| 11 | 2008 | 53 |
About Löıc Matthey
Löıc Matthey is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Biophysics, Cultural Studies and Insect Science, having authored 11 papers that have together received 1.4k indexed citations. Recurring topics across this work include Domain Adaptation and Few-Shot Learning (4 papers), Generative Adversarial Networks and Image Synthesis (2 papers), Machine Learning and Data Classification (2 papers), Modular Robots and Swarm Intelligence (1 paper), Language and cultural evolution (1 paper), Neural dynamics and brain function (1 paper), Neural and Behavioral Psychology Studies (1 paper) and Memory and Neural Mechanisms (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (613 citations), Artificial Intelligence (706 citations), Signal Processing (144 citations), Computer Graphics and Computer-Aided Design (26 citations) and Cognitive Neuroscience (108 citations). Löıc Matthey has collaborated with scholars based in United States, United Kingdom and Switzerland. Frequent co-authors include Alexander Lerchner, Christopher Burgess, Irina Higgins, Matthew Botvinick, Arka Pal, Xavier Glorot, Shakir Mohamed, Paul M. Bays, Peter Dayan and Alcherio Martinoli. Their work appears in journals such as PLoS Computational Biology, Adaptive Agents and Multi-Agents Systems, arXiv (Cornell University), International Conference on Learning Representations 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.