Eric Mitchell

4.5k citations
11 papers · 77 indexed · h-index 5

Impact in

Papers in

Eric Mitchell

9 papers receiving 74 citations

Peers

Eric Mitchell
Comparison fields: 5 of 39
  • Health Informatics 7
  • Structural Biology 4
  • Artificial Intelligence 49
  • Computer Science Applications 4
  • Biophysics 4
Replace Prashant Shah with:
Prashant Shah United States
Ayesha Bajwa Hong Kong
Rajiv Mathews United States
Tosin Adewumi Sweden
Sarah Tan United States
Rafael Rafailov United States
Ninareh Mehrabi United States
Maximin Coavoux France
Nishant Subramani United States
Sohee Yang South Korea
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Citations per field
00.5×1.5×
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Citations per year

Countries citing papers authored by Eric Mitchell

Since Specialization
Citations

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

Fields of papers citing papers by Eric Mitchell

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Eric Mitchell. 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 Eric Mitchell. The network helps show where Eric Mitchell may publish in the future.

Co-authors

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

All Works

11 of 11 papers shown
#Work
1 202337
2 202213
3 20248
4 20236
5 20234
6 20243
7
Higher-Order Function Networks for Learning Composable 3D Object Representations
20202
8
QXplore: Q-Learning Exploration by Maximizing Temporal Difference Error
20192
9 19962
10
Challenges of Acquiring Compositional Inductive Biases via Meta-Learning
20210
11 20240

About Eric Mitchell

Eric Mitchell is a scholar working on Health Informatics, Structural Biology, Computer Graphics and Computer-Aided Design, Artificial Intelligence and Transportation, having authored 11 papers that have together received 77 indexed citations. Recurring topics across this work include Topic Modeling (4 papers), Natural Language Processing Techniques (3 papers), Multimodal Machine Learning Applications (2 papers), Domain Adaptation and Few-Shot Learning (2 papers), Electron and X-Ray Spectroscopy Techniques (1 paper), 3D Shape Modeling and Analysis (1 paper), Image Processing Techniques and Applications (1 paper) and Transportation and Mobility Innovations (1 paper). The work is most often cited by research in Health Informatics (7 citations), Structural Biology (4 citations), Artificial Intelligence (49 citations), Computer Science Applications (4 citations) and Biophysics (4 citations). Eric Mitchell has collaborated with scholars based in United States and South Korea. Frequent co-authors include Chelsea Finn, Christopher D. Manning, Archit Sharma, Rafael Rafailov, Huaxiu Yao, Joseph J. Noh, Ananth Agarwal, Patrick Liu, Will J. Armstrong and Stephan Saalfeld. Their work appears in journals such as Nature Communications, Transportation Research Record Journal of the Transportation Research Board, arXiv (Cornell University) and National Conference on Artificial Intelligence.

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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