Francis Dutil
Impact in
-
- Multimodal Machine Learning Applications
- Generative Adversarial Networks and Image Synthesis
- Advanced Image and Video Retrieval Techniques
- Digital Media Forensic Detection
-
- Topic Modeling
- Natural Language Processing Techniques
- Domain Adaptation and Few-Shot Learning
- Explainable Artificial Intelligence (XAI)
Papers in
-
- Domain Adaptation and Few-Shot Learning 4
- Topic Modeling 3
- Natural Language Processing Techniques 2
- Explainable Artificial Intelligence (XAI) 2
- Machine Learning and Data Classification 2
-
- Multimodal Machine Learning Applications 7
- Generative Adversarial Networks and Image Synthesis 2
- Video Analysis and Summarization 1
- Co-authors
- Sandeep Subramanian (1 shared paper)Sai Rajeswar (1 shared paper)Aaron Courville (1 shared paper)Chris Pal (1 shared paper)Thomas Fevens (2 shared papers)Qicheng Lao (2 shared papers)Mohammad Havaei (2 shared papers)Lisa Di Jorio (2 shared papers)
- Journals
- Pattern Recognition (1 paper)Neural Information Processing Systems (1 paper)arXiv (Cornell University) (1 paper)
- Partner nations
- CanadaUnited StatesUnited Kingdom
In The Last Decade
Francis Dutil
9 papers receiving 121 citations
Peers
Comparison fields: 5 of 43
- Computer Vision and Pattern Recognition 71
- Artificial Intelligence 84
- Health Informatics 2
- Computer Graphics and Computer-Aided Design 3
- Signal Processing 6
Countries citing papers authored by Francis Dutil
This map shows the geographic impact of Francis Dutil'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 Francis Dutil with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Francis Dutil more than expected).
Fields of papers citing papers by Francis Dutil
This network shows the impact of papers produced by Francis Dutil. 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 Francis Dutil. The network helps show where Francis Dutil may publish in the future.
Co-authors
The 15 scholars most cited alongside Francis Dutil, 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 | 2017 | 75 | |
| 2 | 2019 | 19 | |
| 3 | 2021 | 12 | |
| 4 | Plan, Attend, Generate: Planning for Sequence-to-Sequence Models | 2017 | 6 |
| 5 | 2021 | 4 | |
| 6 | Saliency is a Possible Red Herring When Diagnosing Poor Generalization | 2021 | 4 |
| 7 | GradMask: Reduce Overfitting by Regularizing Saliency. | 2019 | 3 |
| 8 | 2017 | 2 | |
| 9 | Underwhelming Generalization Improvements From Controlling Feature Attribution | 2019 | 1 |
About Francis Dutil
Francis Dutil is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Infectious Diseases and Organic Chemistry, having authored 9 papers that have together received 126 indexed citations. Recurring topics across this work include Multimodal Machine Learning Applications (7 papers), Domain Adaptation and Few-Shot Learning (4 papers), Topic Modeling (3 papers), Natural Language Processing Techniques (2 papers), Explainable Artificial Intelligence (XAI) (2 papers), Generative Adversarial Networks and Image Synthesis (2 papers), Machine Learning and Data Classification (2 papers) and Video Analysis and Summarization (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (71 citations), Artificial Intelligence (84 citations), Health Informatics (2 citations), Computer Graphics and Computer-Aided Design (3 citations) and Signal Processing (6 citations). Francis Dutil has collaborated with scholars based in Canada, United States and United Kingdom. Frequent co-authors include Sandeep Subramanian, Sai Rajeswar, Aaron Courville, Chris Pal, Thomas Fevens, Qicheng Lao, Mohammad Havaei, Lisa Di Jorio, Yoshua Bengio and Ahmad Pesaranghader. Their work appears in journals such as Pattern Recognition, Neural Information Processing Systems and arXiv (Cornell University).
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.