Forest Agostinelli
Impact in
- Endocrine and Autonomic Systems top 10%
- Circadian rhythm and melatonin
- Aging top 10%
- Genetics, Aging, and Longevity in Model Organisms
Papers in
-
- Circadian rhythm and melatonin 4
-
- Reinforcement Learning in Robotics 2
- Co-authors
- Pierre Baldi (7 shared papers)Michael R. Anderson (2 shared papers)Honglak Lee (2 shared papers)Alexander Shmakov (2 shared papers)Stephen McAleer (2 shared papers)Nicholas Ceglia (2 shared papers)Paolo Sassone‐Corsi (2 shared papers)Babak Shahbaba (2 shared papers)
- Journals
- Nucleic Acids Research (2 papers)Nature Communications (1 paper)Bioinformatics (1 paper)Nature Machine Intelligence (1 paper)Journal of Materials Science Materials in Electronics (1 paper)
- Partner nations
- United StatesChinaCyprus
In The Last Decade
Forest Agostinelli
14 papers receiving 366 citations
Peers
Comparison fields: 5 of 82
- Endocrine and Autonomic Systems 87
- Aging 21
- Computer Vision and Pattern Recognition 117
- Media Technology 39
- Artificial Intelligence 93
Countries citing papers authored by Forest Agostinelli
This map shows the geographic impact of Forest Agostinelli'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 Forest Agostinelli with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Forest Agostinelli more than expected).
Fields of papers citing papers by Forest Agostinelli
This network shows the impact of papers produced by Forest Agostinelli. 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 Forest Agostinelli. The network helps show where Forest Agostinelli may publish in the future.
Co-authors
The 25 scholars most cited alongside Forest Agostinelli, 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 | Adaptive Multi-Column Deep Neural Networks with Application to Robust Image Denoising | 2013 | 119 |
| 2 | 2019 | 78 | |
| 3 | 2016 | 68 | |
| 4 | 2018 | 34 | |
| 5 | 2022 | 27 | |
| 6 | 2022 | 11 | |
| 7 | 2021 | 11 | |
| 8 | Robust Image Denoising with Multi-Column Deep Neural Networks | 2013 | 8 |
| 9 | Solving the Rubik's Cube with Approximate Policy Iteration | 2018 | 7 |
| 10 | 2012 | 4 | |
| 11 | 2022 | 3 | |
| 12 | 2022 | 2 | |
| 13 | 2016 | 2 | |
| 14 | 2021 | 1 | |
| 15 | 2025 | 0 |
About Forest Agostinelli
Forest Agostinelli is a scholar working on Endocrine and Autonomic Systems, Artificial Intelligence, Computer Networks and Communications, Computer Science Applications and Plant Science, having authored 15 papers that have together received 375 indexed citations. Recurring topics across this work include Circadian rhythm and melatonin (4 papers), Light effects on plants (3 papers), Advanced Semiconductor Detectors and Materials (2 papers), Sparse and Compressive Sensing Techniques (2 papers), Teaching and Learning Programming (2 papers), Advanced Image Processing Techniques (2 papers), Image and Signal Denoising Methods (2 papers) and Reinforcement Learning in Robotics (2 papers). The work is most often cited by research in Endocrine and Autonomic Systems (87 citations), Aging (21 citations), Computer Vision and Pattern Recognition (117 citations), Media Technology (39 citations) and Artificial Intelligence (93 citations). Forest Agostinelli has collaborated with scholars based in United States, China and Cyprus. Frequent co-authors include Pierre Baldi, Michael R. Anderson, Honglak Lee, Alexander Shmakov, Stephen McAleer, Nicholas Ceglia, Paolo Sassone‐Corsi, Babak Shahbaba, Siwei Chen and Yu Liu. Their work appears in journals such as Nucleic Acids Research, Nature Communications, Bioinformatics, Nature Machine Intelligence and Journal of Materials Science Materials in Electronics.
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.