C. Safta

TChem-atm (v2.0.0): scalable performance-portable multiphase atmospheric chemistry
20260 citationsauthor #7
Towards Spatio-Temporal Extrapolation of Phase-Field Simulations with Convolution-Only Neural Networks
20260 citationsauthor #7
Advancing calibration for stochastic agent-based models in epidemiology with Stein variational inference and Gaussian process surrogates
20250 citationsauthor #2
Uncertainty Quantification of Neural Network Models via Langevin Sampling
20250 citationsauthor #1
Detecting outbreaks using a spatial latent field
20250 citationsauthor #1
Bifidelity Karhunen-Loève Expansion Surrogate with Active Learning for Random Fields
20250 citationsauthor #2
Extrapolating Phase-Field Simulations in Space and Time with Purely Convolutional Architectures
20251 citationsauthor #7
Uncertainty quantification of neural network models of evolving processes via Langevin sampling
20253 citationsauthor #1
CONDENSED STEIN VARIATIONAL GRADIENT DESCENT FOR UNCERTAINTY QUANTIFICATION OF NEURAL NETWORKS
20252 citationsauthor #3
A Comparison of Surrogate Constitutive Models for Viscoplastic Creep Simulation of HT-9 Steel
20250 citationsauthor #7
Generalized Transitional Markov Chain Monte Carlo Sampling Technique for Bayesian Inversion of Electromagnetic Data
20250 citationsauthor #6
Accelerating Phase Field Simulations for Liquid Metal De-alloying Using Adaptive Fourier Neural Operators and U-Nets
20240 citationsauthor #7
Detecting Outbreaks Using a Latent Field: Part I -- Spatial Modeling
20241 citationsauthor #1
Calibration verification for stochastic agent-based disease spread models
20242 citationsauthor #5
A novel probabilistic transfer learning strategy for polynomial regression
20241 citationsauthor #6
Bayesian Calibration of Stochastic Agent Based Model via Random Forest
202411 citationsauthor #2
Improving the performance of Stein variational inference through extreme sparsification of physically-constrained neural network models
202410 citationsauthor #3
Deep Learning Models for Accelerating Phase-Field Simulations
20240 citationsauthor #7
A Bayesian Framework for UQ in Dynamical Systems in the Presence of Corrupted Measurements
20240 citationsauthor #1
A Bayesian Calibration Framework with Embedded Model Error for Model Diagnostics
20245 citationsauthor #5
Accelerating Phase Field Simulations Using Adaptive Fourier Neural Operators and U-Nets
20240 citationsauthor #4
Detecting Outbreaks Using a Latent Field: Part II -- Scalable Estimation
20241 citationsauthor #2
Calibration of stochastic agent-based model with Gaussian process surrogate and Stein variational inference
20240 citationsauthor #3
The UQTk C++/Python Toolkit for Uncertainty Quantification: Overview and Applications
20240 citationsauthor #3
Uncertainty Quantification of Graph Convolution Neural Network Models of Evolving Processes
20242 citationsauthor #2
PRIME - A Software Toolkit for the Characterization of Partially Observed Epidemics in a Bayesian Framework
20240 citationsauthor #1
Condensed Stein Variational Gradient Descent for Uncertainty Quantification of Neural Networks
20242 citationsauthor #2
Accelerating Phase Field Simulations Through Time Extrapolation Using Adaptive Fourier Neural Operators and UNets
20240 citationsauthor #3
CSPlib: A performance portable parallel software toolkit for analyzing complex kinetic mechanisms
20240 citationsauthor #3
A switching Kalman filter approach to online mitigation and correction of sensor corruption for inertial navigation
20240 citationsauthor #5
Accelerating phase field simulations through a hybrid adaptive Fourier neural operator with U-net backbone
202415 citationsauthor #7
Bayesian Framework for Forecasting Dynamical Systems in the Presence of Corrupted Data
20240 citationsauthor #1
Bayesian Calibration of Stochastic Agent Based Model via PCA Based Surrogate Modeling
20243 citationsauthor #3
Accelerating Phase Field Modeling Through Hybrid Simulations using Fourier Neural Operators and UNets
20240 citationsauthor #4
Equivariant graph convolutional neural networks for the representation of homogenized anisotropic microstructural mechanical response
20242 citationsauthor #2
Modeling spatio-temporal processes in climate models via functional tensor networks
20230 citationsauthor #1
Industrial PLC Network Modeling and Parameter Identification Using Sensitivity Analysis and Mean Field Variational Inference
20233 citationsauthor #4
Enhancing Polynomial Chaos Expansion Based Surrogate Modeling using a Novel Probabilistic Transfer Learning Strategy
20231 citationsauthor #6
Expressive Surrogate Models via Functional Tensor Networks
20230 citationsauthor #1
A spatially regularized detector for emergent/re-emergent disease outbreaks
20231 citationsauthor #1
Estimating Latent Fields in Stochastic Dynamical Systems - A Case Study of COVID-19 in New Mexico
20230 citationsauthor #1
Development of a Spatially Regularized Detector for Emergent/Re-emergent Disease Outbreaks.
20220 citationsauthor #1
Reverse-mode differentiation in arbitrary tensor network format: with application to supervised learning
20220 citationsauthor #2
Machine learning constitutive models of inelastic materials with microstructure.
20220 citationsauthor #3
Bayesian calibration of interatomic potentials for binary alloys
20224 citationsauthor #5
TChem: A performance portable parallel software toolkit for complex kinetic mechanisms
20227 citationsauthor #5
Quantifying Uncertainty in E3SM via Functional Tensor Network Approximations.
20220 citationsauthor #1
Trajectory design via unsupervised probabilistic learning on optimal manifolds
20224 citationsauthor #1
Trajectory design via unsupervised probabilistic learning on optimal manifolds – Corrigendum
20220 citationsauthor #1
Bayesian Calibration of Interatomic Potential Models for Binary Alloys.
20220 citationsauthor #2
Enhancing polynomial chaos expansion based surrogates through probabilistic transfer learning.
20220 citationsauthor #4
Deep learning and multi-level featurization of graph representations of microstructural data
20225 citationsauthor #2
Transitional Reversible-Jump MCMC for Subsurface Characterization
20220 citationsauthor #6
The UQTk C++/Python Toolkit for Uncertainty Quantification: Overview and Applications.
20220 citationsauthor #4
Graph Convolutional Neural Networks for Modeling Materials with Microstructure.
20220 citationsauthor #1
Studying the Computational Performance of CSP Analysis on Heterogeneous Computing Platforms.
20220 citationsauthor #3
Low-Rank Tensor Network Approximations for Earth System Model.
20210 citationsauthor #1
Generalized Transitional Markov Chain Monte Carlo Sampling Technique for Bayesian Inversion
20210 citationsauthor #7
TChem ? An Open Source Computational Chemistry Software Library for Heterogeneous Computing Platforms.
20210 citationsauthor #1
TChem v3.0 - A Software Toolkit for the Analysis of Complex Kinetic Models.
20214 citationsauthor #1
Mesh-based graph convolutional neural network models of processes with complex initial states
20210 citationsauthor #2
Characterization of Partially Observed Epidemics Through Bayesian Inference - Application to COVID-19 Forecasts.
20210 citationsauthor #3
CSPlib - A Toolkit for the Analysis of ODE/DAE Dynamical Systems and Chemical Kinetic Models.
20210 citationsauthor #3
Dimensionality Reduction and Physics-Informed Neural Networks for Climate Land Models.
20210 citationsauthor #2
Functional Tensor Network Approximations for E3SM Land Model.
20210 citationsauthor #1
The predictive skill of convolutional neural networks models for disease forecasting
202112 citationsauthor #3
Numerical simulations of gaseous flames in combustion chamber applications
20211 citationsauthor #2
Forecasting Multi-Wave Epidemics Through Bayesian Inference
20215 citationsauthor #3
Constrained Gaussian Processes: A Survey.
20211 citationsauthor #4
Polynomial Chaos Expansions for Discrete Random Variables in Cyber Security Emulytics Experiments.
20210 citationsauthor #4
Sensitivity-Informed Bayesian Inference for Home PLC Network Models with Unknown Parameters
20215 citationsauthor #2
Mesh-based graph convolutional neural networks for modeling materials with microstructure
202117 citationsauthor #2
Bayesian calibration of interatomic potential models for binary alloys.
20211 citationsauthor #2
Daily Forecasting of Regional Epidemics of Coronavirus Disease with Bayesian Uncertainty Quantification, United States
202120 citationsauthor #6
Exascale Catalytic Chemistry (ECC).
20210 citationsauthor #9
CSPlib - A Software Toolkit for the Analysis of Dynamical Systems and Chemical Kinetic Models.
20211 citationsauthor #3
Using computational singular perturbation as a diagnostic tool in ODE and DAE systems: a case study in heterogeneous catalysis
20216 citationsauthor #3
Efficient Underground Formation Characterization Using Transitional Markov Chain Monte Carlo Sampling
20202 citationsauthor #6
Rapid Assessment of Autoignition Propensity in Novel Fuels and Blends.
20200 citationsauthor #5
Predictive Skill of Deep Learning Models Trained on Limited Sequence Data.
20203 citationsauthor #1
Transitional Markov Chain Monte Carlo Sampler in UQTk.
20207 citationsauthor #1
Characterization of Partially Observed Epidemics - Application to COVID-19.
20201 citationsauthor #1
Daily Forecasting of New Cases for Regional Epidemics of Coronavirus Disease 2019 with Bayesian Uncertainty Quantification
20203 citationsauthor #6
Bifidelity Gradient-Based Approach for Nonlinear Well-Logging Inverse Problems
20201 citationsauthor #7
LDRD Project Summary: Incorporating physical constraints into Gaussian process surrogate models.
20200 citationsauthor #5
Simulated production of OH, HO2, CH2O, and CO2 during dilute fuel oxidation can predict 1st-stage ignition delays
202017 citationsauthor #2
Palliative Re-Irradiation of Bone Metastases - Case Report
20201 citationsauthor #3
Underground formation characterization and uncertainty quantification using transitional Markov chain Monte Carlo sampling with an efficient parallel implementation
20200 citationsauthor #6
Characterization of partially observed epidemics through Bayesian inference: application to COVID-19
20206 citationsauthor #1
Sandia National Laboratories COVID-19 LDRD Project Summaries.
20200 citationsauthor #12
TChem v2.0 - A Software Toolkit for the Analysis of Complex Kinetic Models.
20202 citationsauthor #1
A Survey of Constrained Gaussian Process Regression: Approaches and Implementation Challenges
2020142 citationsauthor #4
Sandia's Research in Support of COVID-19 Pandemic Response: Computing and Information Sciences.
20201 citationsauthor #8
Efficient Bi-fidelity Gradient-Based Method for Non-Linear Inverse Problems
20200 citationsauthor #6
TChem - A Software Toolkit for the Analysis of Complex Kinetic Models
202036 citationsauthor #1
Uncertainty Quantification for a Turbulent Round Jet Using Multifidelity Karhunen-Loeve Expansions
20205 citationsauthor #3
EGSim - a C++ Toolkit for Analysis of Power Grid Systems.
20191 citationsauthor #2
Progress in Scramjet Design Optimization Under Uncertainty Using Simulations of the HIFiRE Direct Connect Rig
20195 citationsauthor #4
A hybrid, non-split, stiff/RKC, solver for advection–diffusion–reaction equations and its application to low-Mach number combustion
20194 citationsauthor #3
Estimating Regional Methane Emissions Through Atmospheric Measurements and Inverse Modeling.
20190 citationsauthor #1

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