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Model Reduction and Neural Networks

Model Reduction and Neural Networks

154 faculty research Model Reduction and Neural Networks on GradNova.

F
Fernando Teixeira

Academic Director Titles, Electrical and Computer Engineering; Professor, Electrical and Computer Engineering

Department of Electrical and Computer Engineering

The Ohio State University

Electromagnetics
Model Reduction and Neural Networks
Advanced Numerical Methods in Computational Mathematics
Advanced Mathematical Modeling in Engineering
+2
D
Debdipta Goswami

Assistant Professor, Mechanical and Aerospace Engineering; Assistant Professor, Electrical and Computer Engineering

Department of Electrical and Computer Engineering

The Ohio State University

Advanced Memory and Neural Computing
Distributed Control Multi-Agent Systems
Model Reduction and Neural Networks
Neural Networks and Applications
+1
C
Advanced X-Ray Imaging Techniques
Generative Adversarial Networks and Image Synthesis
Image and Signal Denoising Methods
Model Reduction and Neural Networks
+1
F
Fengying Dang

Assistant Professor, Electrical and Computer Engineering; Affiliated Assistant Professor, Mechanical and Aerospace Engineering

Department of Electrical and Computer Engineering

Michigan Technological University

Application of Artificial Intelligence in Robotics
Data-Driven Modeling
Learning-Based Control
Robotics and Control
+7
T
Artificial Intelligence + Machine Learning
Electronic, Magnetic, Optical and Quantum Materials and Devices
Machine Learning in Materials Science
Neural Networks and Applications
+3
L
Luca Daniel

Joseph F. and Nancy P. Keithley Professor in Electrical Engineering and Computer Science, [EE and AI+D]

Department of Electrical Engineering and Computer Science (EECS)

Massachusetts Institute of Technology

Electronic, Magnetic, Optical and Quantum Materials and Devices
Nanoscale Materials, Devices, and Systems
Systems Theory, Control, and Autonomy
Advanced MRI Techniques and Applications
+4
E
Control Systems and Identification
Model Reduction and Neural Networks
Numerical Methods for Differential Equations
Stability and Control of Uncertain Systems
+1
D
Advanced Optimization Algorithms Research
Complex Network Analysis Techniques
Model Reduction and Neural Networks
Sparse and Compressive Sensing Techniques
+1
U
Control Systems and Identification
Model Reduction and Neural Networks
Power System Optimization and Stability
Probabilistic and Robust Engineering Design
+1
K
2D Materials and Applications
Advancements in Semiconductor Devices and Circuit Design
Machine Learning in Materials Science
Model Reduction and Neural Networks
+1
T
3D Shape Modeling and Analysis
Advanced Numerical Analysis Techniques
Advanced Vision and Imaging
Computer Graphics and Visualization Techniques
+1
A
Hydrological Forecasting Using AI
Hydrology and Watershed Management Studies
Model Reduction and Neural Networks
Neural Networks and Applications
+1
S
Artificial Intelligence (ml: Theory and Modeling, Physics-Informed Machine Learning)
Gaussian Processes and Bayesian Inference
Model Reduction and Neural Networks
Tensor Decomposition and Applications
+2
V
Artificial Intelligence (physics-Informed Machine Learning)
Scientific Computing (geometry and Mesh Generation, High-Performance Computing, Modeling Methods and Frameworks)
Model Reduction and Neural Networks
Fluid Dynamics and Turbulent Flows
+3
E
Advanced Numerical Methods in Computational Mathematics
Distributed and Parallel Computing Systems
Lattice Boltzmann Simulation Studies
Model Reduction and Neural Networks
+1
S
Stephen Tu

Assistant Professor of Electrical and Computer Engineering and Computer Science

Ming Hsieh Department of Electrical and Computer Engineering

University of Southern California

Adversarial Robustness in Machine Learning
Formal Methods in Verification
Model Reduction and Neural Networks
Probabilistic and Robust Engineering Design
+1
O
3D Shape Modeling and Analysis
Advanced Numerical Analysis Techniques
Computational Geometry and Mesh Generation
Computer Graphics and Visualization Techniques
+1
P
Fluid Dynamics and Turbulent Flows
Gaussian Processes and Bayesian Inference
Model Reduction and Neural Networks
Neural Networks and Applications
+1
E
Data Mining
Machine Learning
Outlier/anomaly Detection and Explanation
Real Time Data Stream Processing and Analysis
+5
M
Advanced Multi-Objective Optimization Algorithms
Generative Adversarial Networks and Image Synthesis
Model Reduction and Neural Networks
D
Coagulation and Flocculation Studies
Mathematical and Theoretical Epidemiology and Ecology Models
Mathematical Biology Tumor Growth
Model Reduction and Neural Networks
+1
R
Bayesian Modeling and Causal Inference
Gaussian Processes and Bayesian Inference
Model Reduction and Neural Networks
Probabilistic and Robust Engineering Design
+1
S
Adversarial Robustness in Machine Learning
Control and Stability of Dynamical Systems
Microgrid Control and Optimization
Model Reduction and Neural Networks
+1
X
Model Reduction and Neural Networks
Numerical Methods in Inverse Problems
Stochastic Gradient Optimization Techniques
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