Arka Pal
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
- Natural Language Processing Techniques
Papers in
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- Evolutionary Algorithms and Applications 1
- AI in cancer detection 1
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- Genomics and Phylogenetic Studies 1
- Co-authors
- Matthew Botvinick (2 shared papers)Löıc Matthey (2 shared papers)Irina Higgins (2 shared papers)Alexander Lerchner (2 shared papers)Christopher Burgess (2 shared papers)Shakir Mohamed (1 shared paper)Xavier Glorot (1 shared paper)Murray Shanahan (1 shared paper)
- Journals
- International Conference on Learning Representations (1 paper)UCL Discovery (University College London) (1 paper)
- Partner nations
- United StatesUnited KingdomCanada
In The Last Decade
Arka Pal
2 papers receiving 1.1k citations
Arka Pal's Hit Papers
Peers
Comparison fields: 5 of 114
- Computer Vision and Pattern Recognition 578
- Artificial Intelligence 681
- Signal Processing 144
- Computer Graphics and Computer-Aided Design 25
- Biophysics 26
Countries citing papers authored by Arka Pal
This map shows the geographic impact of Arka Pal'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 Arka Pal with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Arka Pal more than expected).
Fields of papers citing papers by Arka Pal
This network shows the impact of papers produced by Arka Pal. 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 Arka Pal. The network helps show where Arka Pal may publish in the future.
Co-authors
The 11 scholars most cited alongside Arka Pal, 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 | 1198 |
| 2 | SCAN: Learning Hierarchical Compositional Visual Concepts | 2018 | 17 |
About Arka Pal
Arka Pal is a scholar working on Artificial Intelligence, Molecular Biology, Computer Vision and Pattern Recognition, Cultural Studies and Infectious Diseases, having authored 2 papers that have together received 1.2k indexed citations. Recurring topics across this work include Genomics and Phylogenetic Studies (1 paper), Language and cultural evolution (1 paper), Digital Media Forensic Detection (1 paper), Generative Adversarial Networks and Image Synthesis (1 paper), Evolutionary Algorithms and Applications (1 paper) and AI in cancer detection (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (578 citations), Artificial Intelligence (681 citations), Signal Processing (144 citations), Computer Graphics and Computer-Aided Design (25 citations) and Biophysics (26 citations). Arka Pal has collaborated with scholars based in United States, United Kingdom and Canada. Frequent co-authors include Matthew Botvinick, Löıc Matthey, Irina Higgins, Alexander Lerchner, Christopher Burgess, Shakir Mohamed, Xavier Glorot, Murray Shanahan, Demis Hassabis and Matko Bošnjak. Their work appears in journals such as International Conference on Learning Representations 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.