Mohammad Emtiyaz Khan

1.3k total citations
20 papers, 164 citations indexed

About

Mohammad Emtiyaz Khan is a scholar working on Artificial Intelligence, Statistics and Probability and Computer Vision and Pattern Recognition. According to data from OpenAlex, Mohammad Emtiyaz Khan has authored 20 papers receiving a total of 164 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Artificial Intelligence, 6 papers in Statistics and Probability and 3 papers in Computer Vision and Pattern Recognition. Recurrent topics in Mohammad Emtiyaz Khan's work include Gaussian Processes and Bayesian Inference (12 papers), Bayesian Methods and Mixture Models (9 papers) and Statistical Methods and Inference (4 papers). Mohammad Emtiyaz Khan is often cited by papers focused on Gaussian Processes and Bayesian Inference (12 papers), Bayesian Methods and Mixture Models (9 papers) and Statistical Methods and Inference (4 papers). Mohammad Emtiyaz Khan collaborates with scholars based in Switzerland, Canada and Japan. Mohammad Emtiyaz Khan's co-authors include Kevin P. Murphy, Benjamin M. Marlin, Guillaume Bouchard, Marilyne Andersen, Shakir Mohamed, Matthias Seeger, Richard E. Turner, Aleksandr Y. Aravkin, Bo Han and Michael P. Friedlander and has published in prestigious journals such as Journal of Building Performance Simulation, Infoscience (Ecole Polytechnique Fédérale de Lausanne) and arXiv (Cornell University).

In The Last Decade

Mohammad Emtiyaz Khan

20 papers receiving 154 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mohammad Emtiyaz Khan Switzerland 9 124 28 24 13 12 20 164
Lujun Li China 7 51 0.4× 9 0.3× 41 1.7× 4 0.3× 30 2.5× 15 126
Matti Kääriäinen Finland 7 119 1.0× 8 0.3× 17 0.7× 2 0.2× 17 1.4× 11 168
Su-In Lee United States 3 95 0.8× 18 0.6× 41 1.7× 13 1.1× 3 150
Paul Komarek United States 4 78 0.6× 17 0.6× 26 1.1× 8 0.7× 6 115
Eleni Sgouritsa Germany 5 128 1.0× 18 0.6× 29 1.2× 13 1.1× 5 143
Joshua V. Dillon United States 8 145 1.2× 10 0.4× 77 3.2× 20 1.7× 9 205
Settimo Termini Italy 6 75 0.6× 18 0.6× 14 0.6× 1 0.1× 8 0.7× 20 152
Yuanyuan Shen China 7 65 0.5× 68 2.4× 12 0.5× 2 0.2× 3 0.3× 21 212
Suriya Gunasekar United States 6 68 0.5× 10 0.4× 43 1.8× 10 0.8× 15 128
Ruitong Huang Canada 7 99 0.8× 10 0.4× 33 1.4× 1 0.1× 22 1.8× 15 124

Countries citing papers authored by Mohammad Emtiyaz Khan

Since Specialization
Citations

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

Fields of papers citing papers by Mohammad Emtiyaz Khan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mohammad Emtiyaz Khan. 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 Mohammad Emtiyaz Khan. The network helps show where Mohammad Emtiyaz Khan may publish in the future.

Co-authorship network of co-authors of Mohammad Emtiyaz Khan

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

All Works

20 of 20 papers shown
1.
Rastogi, Parag, Mohammad Emtiyaz Khan, & Marilyne Andersen. (2021). Evaluating the suitability of regression-based emulators of building performance in practice: a test suite. Journal of Building Performance Simulation. 15(4). 488–506. 7 indexed citations
2.
Pan, Pingbo, et al.. (2020). Continual Deep Learning by Functional Regularisation of Memorable Past. arXiv (Cornell University). 6 indexed citations
3.
Li, Chao, Mohammad Emtiyaz Khan, Zhun Sun, et al.. (2020). Beyond Unfolding: Exact Recovery of Latent Convex Tensor Decomposition Under Reshuffling. Proceedings of the AAAI Conference on Artificial Intelligence. 34(4). 4602–4609. 3 indexed citations
4.
Han, Bo, et al.. (2020). Variational Imitation Learning with Diverse-quality Demonstrations. 1. 9407–9417. 9 indexed citations
5.
Osawa, Kazuki, et al.. (2019). Practical Deep Learning with Bayesian Principles. arXiv (Cornell University). 32. 4287–4299. 15 indexed citations
6.
Wu, Lin, et al.. (2018). Variational Message Passing with Structured Inference Networks.. International Conference on Learning Representations. 1 indexed citations
7.
Khan, Mohammad Emtiyaz, et al.. (2018). Bayesian Nonparametric Poisson-Process Allocation for Time-Sequence Modeling.. International Conference on Artificial Intelligence and Statistics. 1108–1116. 2 indexed citations
8.
Nielsen, Didrik, et al.. (2018). SLANG: Fast Structured Covariance Approximations for Bayesian Deep Learning with Natural Gradient. arXiv (Cornell University). 31. 6245–6255. 8 indexed citations
9.
Khan, Mohammad Emtiyaz & Lin Wu. (2017). Conjugate-Computation Variational Inference : Converting Variational Inference in Non-Conjugate Models to Inferences in Conjugate Models. International Conference on Artificial Intelligence and Statistics. 878–887. 2 indexed citations
10.
Khan, Mohammad Emtiyaz, et al.. (2017). Gaussian-Process-Based Emulators for Building Performance Simulation. Building Simulation Conference proceedings. 9 indexed citations
11.
Khan, Mohammad Emtiyaz, et al.. (2016). Online Collaborative Prediction of Regional Vote Results. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 11. 233–242. 2 indexed citations
12.
Khan, Mohammad Emtiyaz, Pierre Baqué, François Fleuret, & Pascal Fua. (2015). Kullback-Leibler proximal variational inference. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 28. 3402–3410. 8 indexed citations
13.
Khan, Mohammad Emtiyaz. (2014). Decoupled Variational Gaussian Inference. Neural Information Processing Systems. 27. 1547–1555. 3 indexed citations
14.
Khan, Mohammad Emtiyaz, et al.. (2014). Variational Gaussian Inference for Bilinear Models of Count Data. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 330–343. 1 indexed citations
15.
Khan, Mohammad Emtiyaz, et al.. (2014). Scalable Collaborative Bayesian Preference Learning. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 33. 475–483. 4 indexed citations
16.
Khan, Mohammad Emtiyaz, Aleksandr Y. Aravkin, Michael P. Friedlander, & Matthias Seeger. (2013). Fast Dual Variational Inference for Non-Conjugate Latent Gaussian Models. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 951–959. 12 indexed citations
17.
Khan, Mohammad Emtiyaz, Shakir Mohamed, Benjamin M. Marlin, & Kevin P. Murphy. (2012). A Stick-Breaking Likelihood for Categorical Data Analysis with Latent Gaussian Models. International Conference on Artificial Intelligence and Statistics. 610–618. 20 indexed citations
18.
Khan, Mohammad Emtiyaz. (2012). Variational learning for latent Gaussian model of discrete data. Open Collections. 4 indexed citations
19.
Marlin, Benjamin M., Mohammad Emtiyaz Khan, & Kevin P. Murphy. (2011). Piecewise bounds for estimating bernoulli-logistic latent Gaussian models. International Conference on Machine Learning. 633–640. 15 indexed citations
20.
Khan, Mohammad Emtiyaz, Guillaume Bouchard, Kevin P. Murphy, & Benjamin M. Marlin. (2010). Variational bounds for mixed-data factor analysis. Neural Information Processing Systems. 23. 1108–1116. 33 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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