Guido Montúfar

2.3k total citations
30 papers, 291 citations indexed

About

Guido Montúfar is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computational Theory and Mathematics. According to data from OpenAlex, Guido Montúfar has authored 30 papers receiving a total of 291 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Artificial Intelligence, 11 papers in Computer Vision and Pattern Recognition and 7 papers in Computational Theory and Mathematics. Recurrent topics in Guido Montúfar's work include Generative Adversarial Networks and Image Synthesis (8 papers), Model Reduction and Neural Networks (5 papers) and Reinforcement Learning in Robotics (5 papers). Guido Montúfar is often cited by papers focused on Generative Adversarial Networks and Image Synthesis (8 papers), Model Reduction and Neural Networks (5 papers) and Reinforcement Learning in Robotics (5 papers). Guido Montúfar collaborates with scholars based in United States, Germany and United Kingdom. Guido Montúfar's co-authors include Nihat Ay, Wuchen Li, Razvan Pascanu, Yoshua Bengio, Jason Morton, Johannes Rauh, Yu Guang Wang, Yanan Fan, Ming Li and Daniel F. B. Haeufle and has published in prestigious journals such as PLoS Computational Biology, Neural Computation and Journal of Machine Learning Research.

In The Last Decade

Guido Montúfar

27 papers receiving 276 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Guido Montúfar United States	11	142	79	51	39	32	30	291
Junzheng Jiang China	10	137 1.0×	103 1.3×	53 1.0×	21 0.5×	8 0.3×	47	336
Liquan Xiao China	11	71 0.5×	43 0.5×	23 0.5×	51 1.3×	11 0.3×	60	478
Oğuzhan Teke United States	9	184 1.3×	28 0.4×	107 2.1×	33 0.8×	53 1.7×	28	325
D. A. Podoprikhin Russia	6	242 1.7×	176 2.2×	11 0.2×	31 0.8×	12 0.4×	11	411
Ha Q. Nguyen United States	11	153 1.1×	103 1.3×	33 0.6×	12 0.3×	51 1.6×	24	340
Rajib Kumar Jha India	14	155 1.1×	408 5.2×	55 1.1×	19 0.5×	28 0.9×	46	570
Ambedkar Dukkipati India	10	136 1.0×	88 1.1×	100 2.0×	32 0.8×	46 1.4×	43	337
Todd Plantenga United States	8	99 0.7×	90 1.1×	103 2.0×	84 2.2×	21 0.7×	19	340
J. DeFranza United States	3	44 0.3×	29 0.4×	24 0.5×	25 0.6×	10 0.3×	7	279
Klaus Frick Germany	8	44 0.3×	59 0.7×	6 0.1×	13 0.3×	40 1.3×	21	321

Countries citing papers authored by Guido Montúfar

Since Specialization

Citations

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

Fields of papers citing papers by Guido Montúfar

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Guido Montúfar

This figure shows the co-authorship network connecting the top 25 collaborators of Guido Montúfar. A scholar is included among the top collaborators of Guido Montúfar 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 Guido Montúfar. Guido Montúfar is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Montúfar, Guido, et al.. (2024). Function Space and Critical Points of Linear Convolutional Networks. 8(2). 333–362. 2 indexed citations

Müller, Johannes & Guido Montúfar. (2023). Geometry and convergence of natural policy gradient methods. PubMed. 7(S1). 485–523. 2 indexed citations

Montúfar, Guido, et al.. (2022). Sharp Bounds for the Number of Regions of Maxout Networks and Vertices of Minkowski Sums. 6(4). 618–649. 11 indexed citations

Wang, Yanan, Yu Guang Wang, Changyuan Hu, et al.. (2022). Cell graph neural networks enable the precise prediction of patient survival in gastric cancer. npj Precision Oncology. 6(1). 45–45. 35 indexed citations

Montúfar, Guido, et al.. (2020). Wasserstein distance to independence models. CINECA IRIS Institutial research information system (University of Pisa). 12 indexed citations

Arbel, Michael, et al.. (2020). Kernelized Wasserstein Natural Gradient. eScholarship (California Digital Library). 1 indexed citations

Li, Wuchen & Guido Montúfar. (2020). Ricci curvature for parametric statistics via optimal transport. 3(1). 89–117. 9 indexed citations

Wang, Yu Guang, Ming Li, Zheng Ma, et al.. (2020). Haar Graph Pooling. 1. 9952–9962. 11 indexed citations

Li, Wuchen, et al.. (2019). Wasserstein of Wasserstein Loss for Learning Generative Models. eScholarship (California Digital Library). 1716–1725. 7 indexed citations

10.

Wang, Yu Guang, Ming Li, Zheng Ma, et al.. (2019). HaarPooling: Graph Pooling with Compressive Haar Basis. 3 indexed citations

11.

Li, Wuchen & Guido Montúfar. (2018). Natural gradient via optimal transport. 1(2). 181–214. 32 indexed citations

12.

Haeufle, Daniel F. B., et al.. (2016). Evaluating morphological computation in muscle and dc-motor driven models of hopping movements. eScholarship (California Digital Library). 14 indexed citations

13.

Montúfar, Guido. (2015). Deep Narrow Boltzmann Machines are Universal Approximators. International Conference on Learning Representations. 1 indexed citations

14.

Montúfar, Guido, et al.. (2015). A Theory of Cheap Control in Embodied Systems. PLoS Computational Biology. 11(9). e1004427–e1004427. 17 indexed citations

15.

Pascanu, Razvan, Guido Montúfar, & Yoshua Bengio. (2014). On the number of inference regions of deep feed forward networks with piece-wise linear activations. arXiv (Cornell University). 21 indexed citations

16.

Montúfar, Guido, et al.. (2014). Expressive Power of Conditional Restricted Boltzmann Machines. arXiv (Cornell University). 3 indexed citations

17.

Montúfar, Guido & Jason Morton. (2013). Discrete Restricted Boltzmann Machines. Journal of Machine Learning Research. 16(1). 653–672. 3 indexed citations

18.

Montúfar, Guido & Jason Morton. (2012). When Does a Mixture of Products Contain a Product of Mixtures?. arXiv (Cornell University). 1 indexed citations

19.

Montúfar, Guido & Nihat Ay. (2011). Refinements of Universal Approximation Results for Deep Belief Networks and Restricted Boltzmann Machines. Neural Computation. 23(5). 1306–1319. 51 indexed citations

20.

Montúfar, Guido. (2010). Mixture Decomposition of Distributions using a Decomposition of the Sample Space. arXiv (Cornell University). 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.

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