N. Siddharth
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence top 5%
- Signal Processing
- Biomedical Engineering
- Control and Systems Engineering
- Co-authors
- Jeffrey Mark SiskindAndrei BarbuPhilip H. S. TorrBrooks PaigeHaonan YuSven DickinsonSong WangYuewei Lin
- Topics
- Multimodal Machine Learning Applications (9 papers)Generative Adversarial Networks and Image Synthesis (8 papers)Human Pose and Action Recognition (6 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceJournal of Artificial Intelligence ResearchApollo (University of Cambridge)
- Partner nations
- United KingdomUnited StatesMexico
In The Last Decade
N. Siddharth
19 papers receiving 303 citations
Peers
Comparison fields: 5 of 57
- Computer Vision and Pattern Recognition 269
- Artificial Intelligence 212
- Signal Processing 28
- Biomedical Engineering 23
- Control and Systems Engineering 15
Countries citing papers authored by N. Siddharth
This map shows the geographic impact of N. Siddharth'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 N. Siddharth with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites N. Siddharth more than expected).
Fields of papers citing papers by N. Siddharth
This network shows the impact of papers produced by N. Siddharth. 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 N. Siddharth. The network helps show where N. Siddharth may publish in the future.
Co-authorship network of co-authors of N. Siddharth
This figure shows the co-authorship network connecting the top 25 collaborators of N. Siddharth. A scholar is included among the top collaborators of N. Siddharth 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 N. Siddharth. N. Siddharth is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | Relating by Contrasting: A Data-efficient Framework for Multimodal Generative Models | 1 |
| 4 | 3 | |
| 5 | Lessons from reinforcement learning for biological representations of space | 2 |
| 6 | Structured Disentangled Representations | 23 |
| 7 | 12 | |
| 8 | 40 | |
| 9 | DGPose: Disentangled Semi-supervised Deep Generative Models for Human Body Analysis. | 0 |
| 10 | Disentangling Disentanglement | 3 |
| 11 | 1 | |
| 12 | 17 | |
| 13 | Hierarchical Disentangled Representations | 2 |
| 14 | 37 | |
| 15 | Learning Disentangled Representations in Deep Generative Models | 5 |
| 16 | 19 | |
| 17 | 125 | |
| 18 | Seeing Unseeability to See the Unseeable | 1 |
| 19 | 3 | |
| 20 | 16 |
About N. Siddharth
N. Siddharth is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and General Social Sciences, having authored 22 papers that have together received 334 indexed citations. Recurring topics across this work include Multimodal Machine Learning Applications (9 papers), Generative Adversarial Networks and Image Synthesis (8 papers) and Human Pose and Action Recognition (6 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (269 citations), Artificial Intelligence (212 citations) and Signal Processing (28 citations). N. Siddharth has collaborated with scholars based in United Kingdom, United States and Mexico. Frequent co-authors include Jeffrey Mark Siskind, Andrei Barbu, Philip H. S. Torr, Brooks Paige, Haonan Yu, Sven Dickinson, Song Wang, Yuewei Lin, Jan-Willem van de Meent and Alban Desmaison. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Journal of Artificial Intelligence Research and Apollo (University of Cambridge).
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.