Forest Agostinelli

1.1k citations
18 papers · 462 · h-index 10

Impact in

Papers in

Forest Agostinelli

17 papers receiving 451 citations

Peers

Forest Agostinelli
Comparison fields: 5 of 91
  • Endocrine and Autonomic Systems 90
  • Aging 21
  • Computer Vision and Pattern Recognition 138
  • Media Technology 48
  • Artificial Intelligence 128
Replace Zi Wang with:
Zi Wang China
J. Alexander Bae United States
Gye-Young Kim South Korea
Jianjun Wang China
Hrishikesh Deshpande United States
Parvez Ahammad United States
Vinh‐Thong Ta France
Doroteo T. Toledano Spain
Markus Cremer Germany
Hengfu Yang China
Forest Agostinelli relative to Zi Wang China Zi Wang's profile →
Citations per field
00.5×3.8×
Zi Wang · 1×
Citations per year

Countries citing papers authored by Forest Agostinelli

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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.

Border = papers with Forest Agostinelli Line = papers co-authored together Forest Agostinelli links everyone, so they are left out of the graph.

All Works

18 of 18 papers shown
#Work
1
Adaptive Multi-Column Deep Neural Networks with Application to Robust Image Denoising
2013141
2 201986
3 201672
4 201844
5 201834
6 202227
7 202113
8 202211
9
Robust Image Denoising with Multi-Column Deep Neural Networks
20139
10
Solving the Rubik's Cube with Approximate Policy Iteration
20189
11 20224
12 20124
13 20222
14 20162
15 20222
16 20211
17 20221
18 20250

About Forest Agostinelli

Forest Agostinelli is a scholar working on Artificial Intelligence, Endocrine and Autonomic Systems, Computer Networks and Communications, Computer Vision and Pattern Recognition and Computer Science Applications, having authored 18 papers that have together received 462 indexed citations. Recurring topics across this work include Circadian rhythm and melatonin (4 papers), Light effects on plants (3 papers), Reinforcement Learning in Robotics (3 papers), Advanced Semiconductor Detectors and Materials (2 papers), Evolutionary Algorithms and Applications (2 papers), AI in Service Interactions (2 papers), Sparse and Compressive Sensing Techniques (2 papers) and Teaching and Learning Programming (2 papers). The work is most often cited by research in Endocrine and Autonomic Systems (90 citations), Aging (21 citations), Computer Vision and Pattern Recognition (138 citations), Media Technology (48 citations) and Artificial Intelligence (128 citations). Forest Agostinelli has collaborated with scholars based in United States, China and Cyprus. Frequent co-authors include Pierre Baldi, Honglak Lee, Michael R. Anderson, Alexander Shmakov, Stephen McAleer, Nicholas Ceglia, Paolo Sassone‐Corsi, Babak Shahbaba, Sameer Singh and Kristin Eckel‐Mahan. Their work appears in journals such as Nucleic Acids Research, Bioinformatics, Nature Machine Intelligence, Journal of Materials Science Materials in Electronics and Nature Communications.

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.

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