Andrew Silva

450 citations
17 papers · 207 · h-index 8

Impact in

Papers in

Andrew Silva

16 papers receiving 199 citations

Peers

Andrew Silva
Comparison fields: 5 of 60
  • Health Informatics 16
  • Artificial Intelligence 128
  • Safety Research 22
  • Social Psychology 36
  • Computer Vision and Pattern Recognition 25
Replace Hengshuai Yao with:
Hengshuai Yao Canada
Bruno Castro da Silva United States
Serena Booth United States
Rahul Iyer United States
Yasaman Khazaeni United States
Yao Rong Germany
Éloi Zablocki France
Ahmed El Ouadrhiri Morocco
Ben Coppin United Kingdom
Muhammad Rehman Zafar Canada
Andrew Silva relative to Hengshuai Yao Canada Hengshuai Yao's profile →
Citations per field
00.5×3.1×
Hengshuai Yao · 1×
Citations per year

Countries citing papers authored by Andrew Silva

Since Specialization
Citations

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

Fields of papers citing papers by Andrew Silva

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 17 scholars most cited alongside Andrew Silva, 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 Andrew Silva Line = papers co-authored together Andrew Silva links everyone, so they are left out of the graph.

All Works

17 of 17 papers shown
#Work
1 202250
2 202132
3 202230
4 202121
5
Optimization Methods for Interpretable Differentiable Decision Trees Applied to Reinforcement Learning
202018
6 202114
7 201811
8 20229
9 20246
10 20245
11 20234
12
ProLoNets: Neural-encoding Human Experts' Domain Knowledge to Warm Start Reinforcement Learning.
20193
13 20191
14
Personalized Apprenticeship Learning from Heterogeneous Decision-Makers.
20191
15 20231
16 20251
17 20250

About Andrew Silva

Andrew Silva is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Information Systems, Safety Research and Family Practice, having authored 17 papers that have together received 207 indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (6 papers), Explainable Artificial Intelligence (XAI) (6 papers), Topic Modeling (4 papers), Artificial Intelligence in Games (2 papers), Ethics and Social Impacts of AI (2 papers), Machine Learning and Data Classification (2 papers), Natural Language Processing Techniques (1 paper) and Personal Information Management and User Behavior (1 paper). The work is most often cited by research in Health Informatics (16 citations), Artificial Intelligence (128 citations), Safety Research (22 citations), Social Psychology (36 citations) and Computer Vision and Pattern Recognition (25 citations). Andrew Silva has collaborated with scholars based in United States, Canada and United Kingdom. Frequent co-authors include Matthew Gombolay, Nakul Gopalan, Pradyumna Tambwekar, Mariah Schrum, Siddhartha Banerjee, Sonia Chernova, Grace Gombolay, Megha Srivastava, D. A. Pushin and Guy Rosman. Their work appears in journals such as IEEE Robotics and Automation Letters, Journal of Vision, International Journal of Human-Computer Interaction, Autonomous Agents and Multi-Agent Systems and Annals of Clinical and Translational Neurology.

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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