Bhaskara Marthi

2.6k citations
30 papers · 1.6k indexed · h-index 19

Bhaskara Marthi

30 papers receiving 1.5k citations

Peers

Bhaskara Marthi
Comparison fields: 5 of 88
  • Artificial Intelligence 969
  • Computer Vision and Pattern Recognition 518
  • Control and Systems Engineering 376
  • Signal Processing 172
  • Management Science and Operations Research 184
Replace Long-Ji Lin with:
Long-Ji Lin United States
Joseph Modayil Canada
Itsuki Noda Japan
Zuren Feng China
Gerhard Lakemeyer Germany
David Meger Canada
Bilal Piot United Kingdom
Kuk-Hyun Han South Korea
Jing Xiao China
Dan Horgan United Kingdom
Bhaskara Marthi relative to Long-Ji Lin United States Long-Ji Lin's profile →
Citations per field
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Citations per year

Countries citing papers authored by Bhaskara Marthi

Since Specialization
Citations

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

Fields of papers citing papers by Bhaskara Marthi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 2017151
2 2014135
3
Designing intelligent robots : reintegrating AI : papers from the AAAI Spring Symposium
20124
4 201193
5 201132
6 2010118
7 2010126
8
Angelic semantics for high-level actions
200742
9 2007182
10 200761
11 200644
12
A compact, hierarchically optimal Q-function decomposition
20063
13
A compact, hierarchical Q-function decomposition
20061
14
Concurrent hierarchical reinforcement learning
200522
15
Approximate inference for infinite contingent Bayesian networks
200527
16
Super-resolution Enhancement of Video
200384
17
Proceedings Ninth International Conference on Artificial Intelligence and Statistics 2003
20032
18
Decayed MCMC iltering
200218
19
Identity Uncertainty and Citation Matching
2002176
20 200285

About Bhaskara Marthi

Bhaskara Marthi is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Management Science and Operations Research, having authored 30 papers that have together received 1.6k indexed citations. Recurring topics across this work include AI-based Problem Solving and Planning (5 papers), Robotics and Sensor-Based Localization (5 papers), Logic, Reasoning, and Knowledge (4 papers), Reinforcement Learning in Robotics (4 papers), Robotic Path Planning Algorithms (4 papers), Semantic Web and Ontologies (4 papers), Data Quality and Management (4 papers) and Bayesian Modeling and Causal Inference (3 papers). The work is most often cited by research in Artificial Intelligence (969 citations), Computer Vision and Pattern Recognition (518 citations) and Control and Systems Engineering (376 citations). Bhaskara Marthi has collaborated with scholars based in United States, Canada and Netherlands. Frequent co-authors include Stuart Russell, Brian Milch, Jason Wolfe, Sachin Chitta, Hanna Pasula, Kurt Konolige, Eitan Marder-Eppstein, Sarah Osentoski, Scott Niekum and Andrew G. Barto. Their work appears in journals such as Science, The International Journal of Robotics Research and Natural Language Engineering.

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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