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ORCIDVelimir V. Vesselinov
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2020 – today
- 2023
[j10]Daniel O'Malley
, Sarah Y. Greer, Aleksandra Pachalieva, Wu Hao, Dylan Robert Harp, Velimir V. Vesselinov:
DPFEHM: a differentiable subsurface physics simulator. J. Open Source Softw. 8(90): 4560 (2023)- 2022
- [i7]Maruti Kumar Mudunuru, Velimir V. Vesselinov, Bulbul Ahmmed:
GeoThermalCloud: Machine Learning for Geothermal Resource Exploration. CoRR abs/2210.08685 (2022) - 2021
- [j9]B. Ahmmed, Maruti Kumar Mudunuru, Satish Karra, S. C. James, Velimir V. Vesselinov:
A comparative study of machine learning models for predicting the state of reactive mixing. J. Comput. Phys. 432: 110147 (2021) - 2020
- [c3]Maruti Kumar Mudunuru, Daniel O'Malley, Shriram Srinivasan, Jeffrey D. Hyman, Matthew R. Sweeney, Luke Frash, Bill Carey, Michael R. Gross, Nathan J. Welch, Satish Karra, Velimir V. Vesselinov, Qinjun Kang, Hongwu Xu, Rajesh J. Pawar, Tim Carr, Liwei Li, George D. Guthrie, Hari S. Viswanathan:
Physics-Informed Machine Learning for Real-time Reservoir Management. AAAI Spring Symposium: MLPS 2020 - [i6]B. Ahmmed, Maruti Kumar Mudunuru, Satish Karra, S. C. James, Velimir V. Vesselinov:
A Comparative Study of Machine Learning Models for Predicting the State of Reactive Mixing. CoRR abs/2002.11511 (2020)
2010 – 2019
- 2019
- [j8]Velimir V. Vesselinov, Maruti Kumar Mudunuru, Satish Karra, Dan O'Malley, Boian S. Alexandrov:
Unsupervised machine learning based on non-negative tensor factorization for analyzing reactive-mixing. J. Comput. Phys. 395: 85-104 (2019) - [j7]Boian S. Alexandrov, Valentin G. Stanev, Velimir V. Vesselinov, Kim Ø. Rasmussen:
Nonnegative tensor decomposition with custom clustering for microphase separation of block copolymers. Stat. Anal. Data Min. 12(4): 302-310 (2019) - [i5]Daniel O'Malley, John K. Golden, Velimir V. Vesselinov:
Learning to regularize with a variational autoencoder for hydrologic inverse analysis. CoRR abs/1906.02401 (2019) - 2018
- [j6]Zhiming Lu, Velimir V. Vesselinov, Hongzhuan Lei:
Identifying arbitrary parameter zonation using multiple level set functions. J. Comput. Phys. 364: 257-273 (2018) - [j5]Elizabeth Qian, Benjamin Peherstorfer, Daniel O'Malley, Velimir V. Vesselinov, Karen Willcox:
Multifidelity Monte Carlo Estimation of Variance and Sensitivity Indices. SIAM/ASA J. Uncertain. Quantification 6(2): 683-706 (2018) - [i4]Velimir V. Vesselinov, Maruti Kumar Mudunuru, Satish Karra, Dan O'Malley, Boian S. Alexandrov:
Unsupervised Machine Learning Based on Non-Negative Tensor Factorization for Analyzing Reactive-Mixing. CoRR abs/1805.06454 (2018) - 2017
- [c2]Youzuo Lin, Brendt Wohlberg, Velimir V. Vesselinov:
ADMM penalty parameter selection with krylov subspace recycling technique for sparse coding. ICIP 2017: 1945-1949 - [i3]Daniel O'Malley, Velimir V. Vesselinov, Boian S. Alexandrov, Ludmil B. Alexandrov:
Nonnegative/binary matrix factorization with a D-Wave quantum annealer. CoRR abs/1704.01605 (2017) - 2016
- [c1]Daniel O'Malley, Velimir V. Vesselinov:
ToQ.jl: A high-level programming language for D-Wave machines based on Julia. HPEC 2016: 1-7 - [i2]Valentin G. Stanev, Filip L. Iliev, Velimir V. Vesselinov, Boian S. Alexandrov:
Machine learning approach for identification of release sources in advection-diffusion systems. CoRR abs/1612.03948 (2016) - [i1]Filip L. Iliev, Valentin G. Stanev, Velimir V. Vesselinov, Boian S. Alexandrov:
Sources identification using shifted non-negative matrix factorization combined with semi-supervised clustering. CoRR abs/1612.03950 (2016) - 2014
- [j4]Vicky L. Freedman, Xingyuan Chen, Stefan Finsterle, Mark D. Freshley, Ian Gorton, Luke J. Gosink, Elizabeth H. Keating, Carina Lansing, William A. M. Moeglein, Christopher J. Murray, George Shu Heng Pau, Ellen Porter, Sumit Purohit, Mark Rockhold, Karen Schuchardt, Chandrika Sivaramakrishnan, Velimir V. Vesselinov, Scott R. Waichler:
A high-performance workflow system for subsurface simulation. Environ. Model. Softw. 55: 176-189 (2014) - [j3]Daniel O'Malley, Velimir V. Vesselinov:
A Combined Probabilistic/Nonprobabilistic Decision Analysis for Contaminant Remediation. SIAM/ASA J. Uncertain. Quantification 2(1): 607-621 (2014) - 2012
- [j2]Dylan Robert Harp, Velimir V. Vesselinov:
An agent-based approach to global uncertainty and sensitivity analysis. Comput. Geosci. 40: 19-27 (2012) - [j1]Velimir V. Vesselinov, Dylan Robert Harp:
Adaptive hybrid optimization strategy for calibration and parameter estimation of physical process models. Comput. Geosci. 49: 10-20 (2012)
Coauthor Index
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