Jonathan J. Hunt

13.7k citations
30 papers · 5.4k indexed · 1 hit paper · h-index 14

Impact in

Papers in

Jonathan J. Hunt

30 papers receiving 5.3k citations

Hit Papers

Continuous control with deep reinforcement learning 2016 · 4.9k citations
4.9k201620262019202210002.0k3.0k4.0k

Peers

Jonathan J. Hunt
Comparison fields: 5 of 155
  • Artificial Intelligence 2.2k
  • Control and Systems Engineering 1.4k
  • Automotive Engineering 646
  • Computer Networks and Communications 1.0k
  • Computer Vision and Pattern Recognition 838
Replace Hado van Hasselt with:
Hado van Hasselt United Kingdom
Nicolas Heess United Kingdom
Tom Schaul United States
Lucian Buşoniu Romania
J. Zico Kolter United States
Vladimir Stojanović Serbia
Krishna R. Pattipati United States
Qijun Chen China
Ufuk Topcu United States
Marco Pavone United States
Jonathan J. Hunt relative to Hado van Hasselt United Kingdom Hado van Hasselt's profile →
Citations per field
00.5×1.7×
Hado van Hasselt · 1×
Citations per year

Countries citing papers authored by Jonathan J. Hunt

Since Specialization
Citations

This map shows the geographic impact of Jonathan J. Hunt'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 Jonathan J. Hunt with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jonathan J. Hunt more than expected).

Fields of papers citing papers by Jonathan J. Hunt

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jonathan J. Hunt. 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 Jonathan J. Hunt. The network helps show where Jonathan J. Hunt may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Jonathan J. Hunt, 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 Jonathan J. Hunt Line = papers co-authored together Jonathan J. Hunt links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 202312
2 20236
3 20214
4 20184
5
Continuous control with deep reinforcement learning
Hit paper breakdown →
20164888
6 201613
7 201625
8 201521
9 20142
10 201416
11 201321
12 201375
13 20124
14 20126
15 201115
16 201127
17
Natural scene statistics and the development of the primary visual cortex
20111
18 20098
19 200613
20 200160

About Jonathan J. Hunt

Jonathan J. Hunt is a scholar working on Health Informatics, Ophthalmology, Molecular Medicine, Cognitive Neuroscience and Infectious Diseases, having authored 30 papers that have together received 5.4k indexed citations. Recurring topics across this work include Visual perception and processing mechanisms (6 papers), Neural dynamics and brain function (5 papers), Viral gastroenteritis research and epidemiology (4 papers), Ocular Infections and Treatments (4 papers), Reinforcement Learning in Robotics (4 papers), Clostridium difficile and Clostridium perfringens research (4 papers), Ocular Diseases and Behçet’s Syndrome (3 papers) and Antibiotic Resistance in Bacteria (2 papers). The work is most often cited by research in Artificial Intelligence (2.2k citations), Control and Systems Engineering (1.4k citations), Automotive Engineering (646 citations), Computer Networks and Communications (1.0k citations) and Computer Vision and Pattern Recognition (838 citations). Jonathan J. Hunt has collaborated with scholars based in United States, Australia and United Kingdom. Frequent co-authors include David Silver, Timothy Lillicrap, Nicolas Heess, Alexander Pritzel, Yuval Tassa, Daan Wierstra, Tom Erez, Jimmy D. Ballard, Michelle C. Callegan and Brandt Wiskur. Their work appears in journals such as NeuroImage, mSphere, Investigative Ophthalmology & Visual Science, Neural Computation and Journal of the American Chemical Society.

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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