| Differentiable modelling to unify machine learning and physical models for geosciences C Shen, AP Appling, P Gentine, T Bandai, H Gupta, A Tartakovsky, ... Nature Reviews Earth & Environment 4 (8), 552-567, 2023 | 54 | 2023 |
| Physics‐informed neural networks with monotonicity constraints for Richardson‐Richards equation: Estimation of constitutive relationships and soil water flux density from … T Bandai, TA Ghezzehei Water Resources Research, e2020WR027642, 2020 | 51 | 2020 |
| The effect of particle size on thermal and solute dispersion in saturated porous media T Bandai, S Hamamoto, GC Rau, T Komatsu, T Nishimura International Journal of Thermal Sciences 122, 74-84, 2017 | 23 | 2017 |
| Forward and inverse modeling of water flow in unsaturated soils with discontinuous hydraulic conductivities using physics-informed neural networks with domain decomposition T Bandai, TA Ghezzehei Hydrology and Earth System Sciences 26 (16), 4469-4495, 2022 | 22 | 2022 |
| Differentiable modeling to unify machine learning and physical models and advance Geosciences, arXiv C Shen, AP Appling, P Gentine, T Bandai, H Gupta, A Tartakovsky, ... arXiv preprint arXiv:2301.04027, 2023 | 8 | 2023 |
| Characterization of Unsaturated Water Flow in Soils Using Short-Wave Infrared Imaging through Inverse Modeling T Bandai, M Sadeghi, E Babaeian, M Tuller, SB Jones, TA Ghezzehei ASA, CSSA, SSSA International Annual Meeting, 2021 | 1 | 2021 |
| Estimating soil hydraulic properties from oven-dry to full saturation using shortwave infrared imaging and inverse modeling T Bandai, M Sadeghi, E Babaeian, SB Jones, M Tuller, TA Ghezzehei Journal of Hydrology, 131132, 2024 | | 2024 |
| Laboratory Bench-Scale Column Tests on Bentonite Buffer for Geologic Disposal of High-Level Radioactive Waste C Chang, SE Borglin, C Chou, L Zheng, Y Wu, TJ Kneafsey, S Nakagawa, ... AGU23, 2023 | | 2023 |
| Revisiting Scaling Approach to Describe Heterogeneity of Soil Hydraulic Properties through the Lens of Differentiable Modeling T Bandai, M Sadeghi, CI Steefel AGU23, 2023 | | 2023 |
| Model-based interpretation of hydrochemical fluxes from a hillslope in a high-elevation watershed L Stolze, D Dwivedi, B Arora, CI Steefel, T Bandai, Y Wu, PS Nico AGU23, 2023 | | 2023 |
| Differentiable Land Surface Modeling Using JAX P Jiang, P Kidger, G Bisht, T Bandai, KG Pressel, CI Steefel, X Chen AGU23, 2023 | | 2023 |
| Effects of thermal properties of porous media on local thermal (non-) equilibrium heat transport T BANDAI, S HAMAMOTO, GC RAU, T KOMATSU, T NISHIMURA Journal of Groundwater Hydrology 65 (2), 125-139, 2023 | | 2023 |
| Differentiable modeling in Geosciences-Breaking down the imaginary barrier between machine learning and process-based modeling with differentiable modeling C Shen, HV Gupta, T Bandai, D Kifer, AM Tartakovsky, D Feng AGU Fall Meeting Abstracts 2022, H45L-1535, 2022 | | 2022 |
| Inverse modeling of soil moisture dynamics: Estimation of soil hydraulic properties and surface water flux T Bandai University of California, Merced, 2022 | | 2022 |
| Simulation of near-surface soil moisture measurement without boundary conditions using physics-informed neural networks T Ghezzehei, T Bandai AGU Fall Meeting Abstracts 2021, H45E-1225, 2021 | | 2021 |
| Application of physics informed neural networks to near-surface soil moisture dynamics T Bandai, TA Ghezzehei AGU Fall Meeting Abstracts 2020, H166-0007, 2020 | | 2020 |
| Estimation and Forecasting Potential Evapotranspiration Using Limited Hydrometeorological Data TA Ghezzehei, T Bandai AGU Fall Meeting Abstracts 2019, H33L-2120, 2019 | | 2019 |
| Inverse solution of soil water dynamics using physics-constrained machine learning T Bandai, TA Ghezzehei AGU Fall Meeting Abstracts 2019, H31E-02, 2019 | | 2019 |
| Experimental study on the validation of thermal equilibrium assumption between solid and liquid phases in convective heat flow in porous media T Bandai, S Hamamoto, H Imoto, T Nishimura, T Komatsu AGU Fall Meeting Abstracts 2015, H21A-1350, 2015 | | 2015 |
| Estimation of Constitutive Relationships and Soil Water Flux Density from Volumetric Water Content Measurements Using Physics-Informed Neural Networks T Bandai, TA Ghezzehei ASA, CSSA and SSSA International Annual Meetings (2020)| VIRTUAL, 0 | | |
Teamrat A. GhezzeheiUniversity of California, MercedVerified email at ucmerced.edu
