Jeremy Vila

1.0k total citations · 1 hit paper
18 papers, 602 citations indexed

About

Jeremy Vila is a scholar working on Computational Mechanics, Signal Processing and Artificial Intelligence. According to data from OpenAlex, Jeremy Vila has authored 18 papers receiving a total of 602 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Computational Mechanics, 6 papers in Signal Processing and 6 papers in Artificial Intelligence. Recurrent topics in Jeremy Vila's work include Sparse and Compressive Sensing Techniques (7 papers), Blind Source Separation Techniques (6 papers) and Seismic Imaging and Inversion Techniques (5 papers). Jeremy Vila is often cited by papers focused on Sparse and Compressive Sensing Techniques (7 papers), Blind Source Separation Techniques (6 papers) and Seismic Imaging and Inversion Techniques (5 papers). Jeremy Vila collaborates with scholars based in United States, Netherlands and Switzerland. Jeremy Vila's co-authors include Philip Schniter, Mrinal K. Sen, Mauricio Araya‐Polo, Mark Borgerding, Sundeep Rangan, Joseph Meola, Paul Hatchell, Faming Liang, John Solum and Boran Han and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Signal Processing and Geophysics.

In The Last Decade

Jeremy Vila

16 papers receiving 590 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Expectation-Maximization Gaussian-Mixture Approximate Message Passing

2013 356 citations Jeremy Vila, Philip Schniter IEEE Transactions on Signal Processing profile →

Peers

Countries citing papers authored by Jeremy Vila

Since Specialization

Citations

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

Fields of papers citing papers by Jeremy Vila

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jeremy Vila

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

All Works

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18 of 18 papers shown

#	Work	Indexed citations
1	Local Off‐Grid Weather Forecasting With Multi‐Modal Earth Observation Data 2025 ·Journal of Advances in Modeling Earth Systems ·(unknown), (unknown), (unknown), Johannes Jakubik, (unknown), (unknown), Jeremy Vila, Detlef Hohl, Chris Hill, Campbell Watson, Sherrie Wang	0
2	Content-based image retrieval for industrial material images with deep learning and encoded physical properties 2023 ·SHILAP Revista de lepidopterología ·(unknown), (unknown), Jeremy Vila, Nishank Saxena, Detlef Hohl	0
3	Rapid Replication of Best Practices through Machine Learning. Never mind the network, look at the data! 2022 ·(unknown), (unknown), (unknown), (unknown), (unknown), (unknown), Jeremy Vila, (unknown), (unknown)	1
4	Deep learning based gather automated processing of migrated gathers for velocity model building 2021 ·(unknown), Boran Han, (unknown), (unknown), (unknown), Jeremy Vila	1
5	A Robust End-to-end Method for Parametric Curve Tracing via Soft Cosine-similarity-based Objective Function 2021 ·Boran Han, Jeremy Vila	1
6	Minibatch least-squares reverse time migration in a deep-learning framework 2020 ·Geophysics ·(unknown), Jeremy Vila, Mauricio Araya‐Polo, (unknown), (unknown), Mrinal K. Sen	29
7	Estimation of time-lapse timeshifts using machine learning 2020 ·(unknown), (unknown), Paul Hatchell, Jeremy Vila, Kanglin Wang	5
8	Nonlinear state-space modeling approaches to real-time autonomous geosteering 2020 ·Journal of Petroleum Science and Engineering ·(unknown), (unknown), (unknown), Jeremy Vila, Marina Vannucci	4
9	Stochastic clustering and pattern matching for real-time geosteering 2019 ·Geophysics ·(unknown), (unknown), (unknown), (unknown), Marina Vannucci, Jeremy Vila, Faming Liang	4
10	Deep learning applied to seismic attribute computation 2019 ·Interpretation ·(unknown), (unknown), Jeremy Vila, (unknown), John Solum, (unknown), (unknown)	6
11	Classifier Performance Estimation with Unbalanced, Partially Labeled Data 2017 ·Benjamin A. Miller, Jeremy Vila, (unknown), (unknown)	1
12	Generalized approximate message passing for cosparse analysis compressive sensing 2015 ·Mark Borgerding, Philip Schniter, Jeremy Vila, Sundeep Rangan	17
13	An Empirical-Bayes Approach to Recovering Linearly Constrained Non-Negative Sparse Signals 2014 ·IEEE Transactions on Signal Processing ·Jeremy Vila, Philip Schniter	30
14	Expectation-Maximization Gaussian-Mixture Approximate Message Passing breakdown → 2013 ·IEEE Transactions on Signal Processing ·Jeremy Vila, Philip Schniter	356
15	Hyperspectral image unmixing via bilinear generalized approximate message passing 2013 ·Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE ·Jeremy Vila, Philip Schniter, Joseph Meola	6
16	An empirical-bayes approach to recovering linearly constrained non-negative sparse signals 2013 ·Jeremy Vila, Philip Schniter	5
17	Expectation-maximization Gaussian-mixture approximate message passing 2012 ·Jeremy Vila, Philip Schniter	51
18	Expectation-maximization Bernoulli-Gaussian approximate message passing 2011 ·Jeremy Vila, Philip Schniter	85

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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