Publications: AML-CS

20262 papers

PyTEDA-web: A FastAPI platform for interactive data assimilation benchmarking with real-time streaming and persistent experiment tracking

Nino-Ruiz, E. D.

SoftwareX, 34, 102738 · Elsevier

SoftwareRead

Language development and inequality in early childhood: a study in Caribbean Colombian contexts

Nino-Ruiz, E. D. et al.

Vulnerable Children and Youth Studies · Taylor & Francis

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20253 papers

TEDA: A lightweight Python framework for educational data assimilation

Nino-Ruiz, E. D.

SoftwareX, 31, 102297 · Elsevier

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Improved Rosenbrock method with error estimator and Jacobian approximation using complex step

Perez Rivera, J. D., Turizo, D., Nino-Ruiz, E. D., Montoya, O. D.

Results in Applied Mathematics, 27, 100629 · Elsevier

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Statistical package for computing precision covariance matrices via modified Cholesky decomposition

Nino-Ruiz, E. D., Cabarcas Arrieta, D. S., Fernandez Quiroz, G. R., Quintero, N.

SoftwareX, 30, 102125 · Elsevier

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20233 papers

A Stochastic Covariance Shrinkage Approach in Ensemble Transform Kalman Filtering

Popov, A. A., Sandu, A., Nino-Ruiz, E. D., Evensen, G.

Tellus A: Dynamic Meteorology and Oceanography, 75(1), 159–171

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AMLCS-DA: A data assimilation package in Python for Atmospheric General Circulation Models

Nino-Ruiz, E. D., Consuegra Ortega, R. S.

SoftwareX · Elsevier

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Ensemble based methods for leapfrog integration in the simplified parameterizations, primitive-equation dynamics model

Nino-Ruiz, E. D., Consuegra Ortega, R. S., Lucini, M.

Quarterly Journal of the Royal Meteorological Society · RMetS

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20222 papers

Ensemble Driven Shrinkage Covariance Matrix Estimation for Sequential Data Assimilation

Nino-Ruiz, E. D., Guzman, L., Jabba, D.

International Journal of Artificial Intelligence, 20(2) · CESER

Journal

TEDA: A Computational Toolbox for Teaching Ensemble Based Data Assimilation

Nino-Ruiz, E. D., Valbuena, S. R.

Computational Science – ICCS 2022, Lecture Notes in Computer Science, vol. 13353 · Springer

Conference

20215 papers

A line-search optimization method for non-Gaussian data assimilation via random quasi-orthogonal sub-spaces

Nino-Ruiz, E. D.

Journal of Computational Science, 53, 101373 · Elsevier

Journal

An efficient ensemble Kalman Filter implementation via shrinkage covariance matrix estimation: exploiting prior knowledge

Lopez-Restrepo, S., Nino-Ruiz, E. D., Guzman-Reyes, L. G., Yarce, A., Pinel, N., Heemink, A. W.

Computational Geosciences, 25(3), 985–1003 · Springer

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A data-driven localization method for ensemble based data assimilation

Nino-Ruiz, E. D.

Journal of Computational Science, 51, 101328 · Elsevier

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An ensemble Kalman filter implementation based on the Ledoit and Wolf covariance matrix estimator

Nino-Ruiz, E. D., Guzman, L., Jabba, D.

Journal of Computational and Applied Mathematics, 384, 113163 · Elsevier

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Data-Driven Methods for Weather Forecast

Nino-Ruiz, E. D., Acevedo García, F. J.

International Conference on Computational Science (ICCS), pp. 326–336 · Springer

Conference

20207 papers

On the mathematical modelling and data assimilation for air pollution assessment in the Tropical Andes

Montoya, O. L., Niño-Ruiz, E. D., Pinel, N.

Environmental Science and Pollution Research, 27(29), 35993–36012 · Springer

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A numerical method for solving linear systems in the preconditioned Crank–Nicolson algorithm

Nino-Ruiz, E. D.

Applied Mathematics Letters, 104, 106254 · Elsevier

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An adjoint-free four-dimensional variational data assimilation method via a modified Cholesky decomposition and an iterative Woodbury matrix formula

Nino-Ruiz, E. D., Guzman-Reyes, L. G., Beltran-Arrieta, R.

Nonlinear Dynamics, 99(3), 2441–2457 · Springer

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A Maximum Likelihood Ensemble Filter via a Modified Cholesky Decomposition for Non-Gaussian Data Assimilation

Nino-Ruiz, E. D., Mancilla-Herrera, A., Lopez-Restrepo, S., Quintero-Montoya, O.

Sensors, 20(3), 877 · MDPI

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A Four Dimensional Variational Data Assimilation Framework for Wind Energy Potential Estimation

Nino-Ruiz, E. D., Calabria-Sarmiento, J. C., Guzman-Reyes, L. G., Henao, A.

Atmosphere, 11(2), 167 · MDPI

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Hybrid Ensemble Kalman Filter and Markov Chain Monte Carlo Implementations for Non-Gaussian Data Assimilation

Nino-Ruiz, E. D.

International Journal of Artificial Intelligence, 18(2) · CESER

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A Random Line-Search Optimization Method via Modified Cholesky Decomposition for Non-linear Data Assimilation

Nino-Ruiz, E. D.

International Conference on Computational Science (ICCS), pp. 189–202 · Springer

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20199 papers

Dynamic Site Response Characterization Via Bayesian Inference: Analysis of the SGC Station Deposit in Bogota, Colombia

Mercado, V., Nino, E. D., Arteta, C. A.

Journal of Earthquake Engineering, 23(10), 1629–1650 · Taylor & Francis

Journal

Improved Tabu Search and Simulated Annealing methods for nonlinear data assimilation

Nino-Ruiz, E. D., Yang, X.-S.

Applied Soft Computing, 83, 105624 · Elsevier

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Non-linear data assimilation via trust region optimization

Nino-Ruiz, E. D.

Computational and Applied Mathematics, 38(3), 1–26 · Springer

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A parallel implementation of the ensemble Kalman filter based on modified Cholesky decomposition

Nino-Ruiz, E. D., Sandu, A., Deng, X.

Journal of Computational Science, 36, 100654 · Elsevier

Journal

A Tabu Search implementation for adaptive localization in ensemble-based methods

Nino-Ruiz, E. D., Morales-Retat, L. E.

Soft Computing, 23(14), 5519–5535 · Springer

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A reduced-space line-search method for unconstrained optimization via random descent directions

Nino-Ruiz, E. D., Ardila, C., Estrada, J., Capacho, J.

Applied Mathematics and Computation, 341, 15–30 · Elsevier

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Efficient parallel implementation of DDDAS inference using an ensemble Kalman filter with shrinkage covariance matrix estimation

Nino-Ruiz, E. D., Sandu, A.

Cluster Computing, 22(1), 2211–2221 · Springer

Journal

Water Cycle Algorithm: Implementation and Analysis of Solutions to the Bi-Objective Travelling Salesman Problem

Pimentel, J., Ardila, C. J., Niño, E., Jabba, D., Ruiz-Rangel, J.

International Journal of Artificial Intelligence, 17(2) · CESER

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Container-based architecture for optimal face-recognition tasks in edge computing

Tellez, N., Jimeno, M., Salazar, A., Nino-Ruiz, E. D.

4th ACM/IEEE Symposium on Edge Computing, pp. 301–303

Conference

20185 papers

Local search methods for the solution of implicit inverse problems

Nino-Ruiz, E. D., Ardila, C., Capacho, R.

Soft Computing, 22(14), 4819–4832 · Springer

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Implicit surrogate models for trust region based methods

Nino-Ruiz, E. D.

Journal of Computational Science, 26, 264–274 · Elsevier

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An ensemble Kalman filter implementation based on modified Cholesky decomposition for inverse covariance matrix estimation

Nino-Ruiz, E. D., Sandu, A., Deng, X.

SIAM Journal on Scientific Computing, 40(2), A867–A886 · SIAM

Journal

A Robust Non-Gaussian Data Assimilation Method for Highly Non-Linear Models

Nino-Ruiz, E. D., Cheng, H., Beltran, R.

Atmosphere, 9(4), 126 · MDPI

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Non-Gaussian data assimilation via modified Cholesky decomposition

Nino-Ruiz, E. D., Mancilla-Herrera, A. M., Beltran-Arrieta, R.

7th International Conference on Computers Communications and Control (ICCCC), pp. 29–36 · IEEE

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20174 papers

Robust Data Assimilation Using L1 and Huber Norms

Rao, V., Sandu, A., Ng, M., Nino-Ruiz, E. D.

SIAM Journal on Scientific Computing, 39(3), B548–B570 · SIAM

Journal

A Matrix-Free Posterior Ensemble Kalman Filter Implementation Based on a Modified Cholesky Decomposition

Nino-Ruiz, E. D.

Atmosphere, 8, 125 · MDPI

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A Surrogate Model Based on Mixtures of Taylor Expansions for Trust Region Based Methods

Nino-Ruiz, E. D., Ardila, C. J., Mancilla, A., Estrada, J.

Procedia Computer Science, 108, 1473–1482 (ICCS) · Best Workshop Paper Award

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A Posterior Ensemble Kalman Filter Based on a Modified Cholesky Decomposition

Nino-Ruiz, E. D., Mancilla, A., Calabria, J. C.

Procedia Computer Science, 108, 2049–2058 (ICCS)

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20163 papers

A high-performance computing framework for analyzing the economic impacts of wind correlation

Petra, C. G., Zavala, V. M., Nino-Ruiz, E. D., Anitescu, M.

Electric Power Systems Research, 141, 372–380 · Elsevier

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A derivative-free trust region framework for variational data assimilation

Nino-Ruiz, E. D., Sandu, A.

Journal of Computational and Applied Mathematics, 293, 164–179 · Elsevier

Journal

A novel framework for the parallel solution of combinatorial problems implementing tabu search and simulated annealing algorithms

Guzman, L. G., Nino-Ruiz, E. D., Ardila, C. J., Jabba, D., Nieto, W.

6th International Conference on Computers Communications and Control (ICCCC), pp. 259–263 · IEEE

Conference

20154 papers

Ensemble Kalman filter implementations based on shrinkage covariance matrix estimation

Nino-Ruiz, E. D., Sandu, A.

Ocean Dynamics, 65(11), 1423–1439 · Springer

Journal

An efficient implementation of the ensemble Kalman filter based on an iterative Sherman–Morrison formula

Nino-Ruiz, E. D., Sandu, A., Anderson, J.

Statistics and Computing, 25(3), 561–577 · Springer

Journal

An efficient parallel implementation of the ensemble Kalman filter based on shrinkage covariance matrix estimation

Nino-Ruiz, E. D., Sandu, A.

IEEE 22nd International Conference on High Performance Computing Workshops (HiPCW)

Conference

A parallel ensemble Kalman filter implementation based on modified Cholesky decomposition

Nino-Ruiz, E. D., Sandu, A., Deng, X.

6th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems (ScalA), pp. 1–8

Conference

20141 papers

Variational Data Assimilation Based on Derivative-Free Optimization

Nino, E. D., Sandu, A.

International Conference on Dynamic Data-Driven Environmental Systems Science, pp. 239–250 · Springer

Conference

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