Tapan Mukerji
Ocean Engineering · 2001–2018
A researcher in the Science corpus: 10 papers; trusts 13 researchers and is trusted by 23 researchers here, as inferred from the citation graph.
Subfields
- Ocean Engineering — 29 citations into it; #287 of 3,193 by trust here, #242 by citations
- Geophysics — 27 citations into it; #286 of 1,958 by trust here, #389 by citations
- Mechanical Engineering — 24 citations into it; #1,984 of 8,300 by trust here, #3,966 by citations
- Environmental Engineering — 22 citations into it
- Artificial Intelligence — 16 citations into it
- Statistics and Probability — 13 citations into it
- Mathematical Physics — 7 citations into it
- Probabilistic & Bayesian Methods — 6 citations into it
Whom Tapan Mukerji trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Jef Caers
- R. Bachrach
- E. González
- Gregoire Mariethoz
- Albert Tarantola
- Philippe Renard
- Stuart Geman
- A. Alcolea
- Eric Laloy
Who trusts Tapan Mukerji overall
- M. Bosch
- Dario Grana
- Claudio Madonna
- Hasan Karakul
- E. David
- Niklas Linde
- Joshua A. White
- A. Murmu
- E. González
- R. Bachrach
Papers from Tapan Mukerji's perspective
Ordered by how strongly the researchers Tapan Mukerji trusts endorse each paper. Same corpus, a different order for every researcher.
- The Probability Perturbation Method: A New Look at Bayesian Inverse Modeling
- Multiple-Point Simulations Constrained by Continuous Auxiliary Data
- Blocking Moving Window algorithm: Conditioning multiple‐point simulations to hydrogeological data
- Comparing the Gradual Deformation with the Probability Perturbation Method for Solving Inverse Problems
- Bayesian inverse problem and optimization with iterative spatial resampling
- Seismic inversion combining rock physics and multiple-point geostatistics
- Gradual Deformation and Iterative Calibration of Gaussian-Related Stochastic Models
- High‐dimensional posterior exploration of hydrologic models using multiple‐try DREAM(ZS) and high‐performance computing
- Multiple-point Geostatistics: Stochastic Modeling with Training Images
- Probability theory: the logic of science
Their papers
- Convolutional neural network for seismic impedance inversion (2018) — 404 citations
- Geological realism in hydrogeological and geophysical inverse modeling: A review (2015) — 195 citations
- Digital rock physics benchmarks - part II: Computing effective properties (2013) — 545 citations
- Digital rock physics benchmarks - Part I: Imaging and segmentation (2013) — 645 citations
- Seismic inversion for reservoir properties combining statistical rock physics and geostatistics: A review (2010) — 445 citations
- The Rock Physics Handbook: Contents (2009) — 1,751 citations
- Seismic inversion combining rock physics and multiple-point geostatistics (2008) — 145 citations
- Quantitative Seismic Interpretation: Applying Rock Physics Tools to Reduce Interpretation Risk (2005) — 771 citations
- Permeability prediction from thin sections: 3D reconstruction and Lattice‐Boltzmann flow simulation (2004) — 152 citations
- Statistical rock physics: Combining rock physics, information theory, and geostatistics to reduce uncertainty in seismic reservoir characterization (2001) — 143 citations