Alexander Lerchner
Impact in
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- Generative Adversarial Networks and Image Synthesis
- Multimodal Machine Learning Applications
- Artificial Intelligence top 2%
- Domain Adaptation and Few-Shot Learning
- Topic Modeling
- Anomaly Detection Techniques and Applications
- Adversarial Robustness in Machine Learning
Papers in
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- Domain Adaptation and Few-Shot Learning 4
- Machine Learning and Data Classification 2
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- Neural dynamics and brain function 6
- Visual perception and processing mechanisms 2
- Co-authors
- Löıc Matthey (8 shared papers)Christopher Burgess (5 shared papers)Irina Higgins (5 shared papers)Matthew Botvinick (4 shared papers)Arka Pal (2 shared papers)Shakir Mohamed (1 shared paper)Xavier Glorot (1 shared paper)John Hertz (4 shared papers)
- Journals
- Neurocomputing (3 papers)Neural Computation (2 papers)Network Computation in Neural Systems (1 paper)arXiv (Cornell University) (3 papers)UCL Discovery (University College London) (1 paper)
- Partner nations
- United StatesUnited KingdomDenmark
In The Last Decade
Alexander Lerchner
15 papers receiving 1.3k citations
Alexander Lerchner's Hit Papers
Peers
Comparison fields: 5 of 115
- Computer Vision and Pattern Recognition 623
- Artificial Intelligence 717
- Signal Processing 146
- Statistical and Nonlinear Physics 109
- Cognitive Neuroscience 158
Countries citing papers authored by Alexander Lerchner
This map shows the geographic impact of Alexander Lerchner'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 Alexander Lerchner with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Alexander Lerchner more than expected).
Fields of papers citing papers by Alexander Lerchner
This network shows the impact of papers produced by Alexander Lerchner. 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 Alexander Lerchner. The network helps show where Alexander Lerchner may publish in the future.
Co-authors
The 25 scholars most cited alongside Alexander Lerchner, 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 | beta-VAE: Learning Basic Visual Concepts with a Constrained Variational Framework Hit paper breakdown → | 2017 | 1219 |
| 2 | 2006 | 34 | |
| 3 | 2006 | 21 | |
| 4 | 2006 | 21 | |
| 5 | Life-Long Disentangled Representation Learning with Cross-Domain Latent Homologies | 2018 | 18 |
| 6 | SCAN: Learning Hierarchical Compositional Visual Concepts | 2018 | 17 |
| 7 | 2004 | 15 | |
| 8 | Multi-Object Representation Learning with Iterative Variational Inference | 2019 | 13 |
| 9 | 2021 | 6 | |
| 10 | 2024 | 6 | |
| 11 | Unsupervised Model Selection for Variational Disentangled Representation Learning | 2020 | 5 |
| 12 | 2021 | 4 | |
| 13 | A Heuristic for Unsupervised Model Selection for Variational Disentangled Representation Learning. | 2019 | 1 |
| 14 | 2004 | 1 | |
| 15 | 2004 | 1 |
About Alexander Lerchner
Alexander Lerchner is a scholar working on Artificial Intelligence, Cognitive Neuroscience, Computer Vision and Pattern Recognition, Statistical and Nonlinear Physics and Molecular Biology, having authored 15 papers that have together received 1.4k indexed citations. Recurring topics across this work include Neural dynamics and brain function (6 papers), Domain Adaptation and Few-Shot Learning (4 papers), stochastic dynamics and bifurcation (4 papers), Generative Adversarial Networks and Image Synthesis (3 papers), Photoreceptor and optogenetics research (2 papers), Machine Learning and Data Classification (2 papers), Advanced Image and Video Retrieval Techniques (2 papers) and Visual perception and processing mechanisms (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (623 citations), Artificial Intelligence (717 citations), Signal Processing (146 citations), Statistical and Nonlinear Physics (109 citations) and Cognitive Neuroscience (158 citations). Alexander Lerchner has collaborated with scholars based in United States, United Kingdom and Denmark. Frequent co-authors include Löıc Matthey, Christopher Burgess, Irina Higgins, Matthew Botvinick, Arka Pal, Shakir Mohamed, Xavier Glorot, John Hertz, Søren Enemark and Daniel Zoran. Their work appears in journals such as Neurocomputing, Neural Computation, Network Computation in Neural Systems, arXiv (Cornell University) and UCL Discovery (University College London).
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.