Igor Mordatch

7.2k citations
32 papers · 1.7k · 2 hit papers · h-index 22

Impact in

Papers in

Igor Mordatch

30 papers receiving 1.7k citations

Igor Mordatch's Hit Papers

Emergence of Grounded Compositional Language in Multi-Agent Populations 2018 · 249 citations
2490+4+9Years since publication100200300

Peers

Igor Mordatch
Comparison fields: 5 of 96
  • Computer Vision and Pattern Recognition 819
  • Control and Systems Engineering 828
  • Computer Graphics and Computer-Aided Design 91
  • Human-Computer Interaction 135
  • Artificial Intelligence 542
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Monica Nicolescu United States
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Ashis G. Banerjee United States
Ning Xi China
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Citations per year

Countries citing papers authored by Igor Mordatch

Since Specialization
Citations

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

Fields of papers citing papers by Igor Mordatch

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 32 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Discovery of complex behaviors through contact-invariant optimization
Hit paper breakdown →
2012308
2
Emergence of Grounded Compositional Language in Multi-Agent Populations
Hit paper breakdown →
2018249
3 2010182
4 2010124
5
Implicit Generation and Modeling in Energy-Based Models
201978
6 201776
7 202266
8 201466
9 200965
10 201564
11 200858
12 201356
13 201354
14
Interactive control of diverse complex characters with neural networks
201549
15 201537
16 201030
17 200828
18 201227
19 201624
20
Compositional Visual Generation with Energy Based Models
202023

About Igor Mordatch

Igor Mordatch is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Control and Systems Engineering, Biomedical Engineering and Cultural Studies, having authored 32 papers that have together received 1.7k indexed citations. Recurring topics across this work include Human Motion and Animation (11 papers), Human Pose and Action Recognition (11 papers), Reinforcement Learning in Robotics (8 papers), Robotic Locomotion and Control (7 papers), Artificial Intelligence in Games (3 papers), Generative Adversarial Networks and Image Synthesis (3 papers), Robot Manipulation and Learning (3 papers) and Robotic Path Planning Algorithms (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (819 citations), Control and Systems Engineering (828 citations), Computer Graphics and Computer-Aided Design (91 citations), Human-Computer Interaction (135 citations) and Artificial Intelligence (542 citations). Igor Mordatch has collaborated with scholars based in United States, Canada and Germany. Frequent co-authors include Pieter Abbeel, Emanuel Todorov, Martin de Lasa, Aaron Hertzmann, Zoran Popović, Yilun Du, Azam Khan, Emo Todorov, Kendall Lowrey and George Fitzmaurice. Their work appears in journals such as ACM Transactions on Graphics, Microscopy and Microanalysis, Cognitive Science, Neural Information Processing Systems and International Conference on Machine Learning.

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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