Emilio Parisotto

2.3k total citations
8 papers, 162 citations indexed

About

Emilio Parisotto is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Information Systems. According to data from OpenAlex, Emilio Parisotto has authored 8 papers receiving a total of 162 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Artificial Intelligence, 2 papers in Computer Vision and Pattern Recognition and 1 paper in Information Systems. Recurrent topics in Emilio Parisotto's work include Reinforcement Learning in Robotics (3 papers), Artificial Intelligence in Games (1 paper) and Blind Source Separation Techniques (1 paper). Emilio Parisotto is often cited by papers focused on Reinforcement Learning in Robotics (3 papers), Artificial Intelligence in Games (1 paper) and Blind Source Separation Techniques (1 paper). Emilio Parisotto collaborates with scholars based in United States, Israel and Canada. Emilio Parisotto's co-authors include Jakob Foerster, Vincent Dumoulin, Sarath Chandar, Marc G. Bellemare, Michael Bowling, Marc Lanctot, Neil Burch, Subhodeep Moitra, Edward Hughes and Nolan Bard and has published in prestigious journals such as Artificial Intelligence, arXiv (Cornell University) and International Conference on Machine Learning.

In The Last Decade

Emilio Parisotto

7 papers receiving 154 citations

Peers

Emilio Parisotto
Chris Martens United States
Jesmin Jahan Tithi United States
H. Niewiadomski Switzerland
Megha Srivastava United States
Jen-tse Huang China
Ashwin Kalyan United States
Mor Geva United States
Nouha Dziri United States
Fatemehsadat Mireshghallah United States
Samuel Weinbach United States
Chris Martens United States
Emilio Parisotto
Citations per year, relative to Emilio Parisotto Emilio Parisotto (= 1×) peers Chris Martens

Countries citing papers authored by Emilio Parisotto

Since Specialization
Citations

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

Fields of papers citing papers by Emilio Parisotto

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Emilio Parisotto

This figure shows the co-authorship network connecting the top 25 collaborators of Emilio Parisotto. A scholar is included among the top collaborators of Emilio Parisotto based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Emilio Parisotto. Emilio Parisotto is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

8 of 8 papers shown
1.
Gu, Albert, et al.. (2023). Structured State Space Models for In-Context Reinforcement Learning. 47016–47031.
2.
Parisotto, Emilio & Russ R. Salakhutdinov. (2021). Efficient Transformers in Reinforcement Learning using Actor-Learner Distillation. arXiv (Cornell University). 1 indexed citations
3.
Parisotto, Emilio, Francis Song, Jack W. Rae, et al.. (2020). Stabilizing Transformers for Reinforcement Learning. International Conference on Machine Learning. 1. 7487–7498. 9 indexed citations
4.
Bard, Nolan, Jakob Foerster, Sarath Chandar, et al.. (2019). The Hanabi challenge: A new frontier for AI research. Artificial Intelligence. 280. 103216–103216. 100 indexed citations
5.
Lee, Lisa, Emilio Parisotto, Devendra Singh Chaplot, & Ruslan Salakhutdinov. (2018). LSTM Iteration Networks: An Exploration of Differentiable Path Finding. International Conference on Learning Representations. 3 indexed citations
6.
Chaplot, Devendra Singh, Emilio Parisotto, & Ruslan Salakhutdinov. (2018). Active Neural Localization. International Conference on Learning Representations. 10 indexed citations
7.
Parisotto, Emilio, Abdelrahman Mohamed, Rishabh Singh, et al.. (2016). Neuro-Symbolic Program Synthesis. arXiv (Cornell University). 38 indexed citations
8.
Parisotto, Emilio, et al.. (2015). EEG dimensionality reduction in automatic identification of synonymy. 2010. 847–851. 1 indexed citations

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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Chris Martens Breakdown of academic impact, for papers by Jesmin Jahan Tithi Breakdown of academic impact, for papers by H. Niewiadomski Breakdown of academic impact, for papers by Megha Srivastava Breakdown of academic impact, for papers by Jen-tse Huang Breakdown of academic impact, for papers by Ashwin Kalyan Breakdown of academic impact, for papers by Mor Geva Breakdown of academic impact, for papers by Nouha Dziri Breakdown of academic impact, for papers by Fatemehsadat Mireshghallah Breakdown of academic impact, for papers by Samuel Weinbach
Rankless by CCL
2026