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#Physics Informed Neural Networks

Showing: 23 courses
Alan Turing Institute

Enhancing Scientific Computing Through Physics-Informed Neural Networks

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Explore physics-informed neural networks (PINNs) as an alternative to traditional scientific computation, addressing challenges in high-dimensional problems and incorporating noisy data in inverse problems.
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1 Lesons
1 hour 10 minutes
On-Demand
Free-Video
Alan Turing Institute

PECANNs - Physics and Equality Constrained Artificial Neural Networks

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Innovative approach to physics-informed neural networks using constrained optimization, addressing hyperparameter challenges and improving accuracy for scientific applications involving multi-dimensional PDEs.
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1 Lesons
58 minutes
On-Demand
Free-Video
Alan Turing Institute

HypoSVI- Earthquake Hypocentre Inversion With Stein Variational Inference and Physics Informed Neural Networks

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Explore physics-informed deep learning for environmental sciences, covering PINNs for Eikonal equations, probabilistic inversion for earthquake location, and neural operators for in-ice navigation.
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1 Lesons
50 minutes
On-Demand
Free-Video
Alan Turing Institute

Emulating InterStellar Medium Chemistry with Physics Informed Neural Networks

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Exploring Physics Informed Neural Networks to emulate InterStellar Medium chemistry, focusing on Giant Molecular Clouds formation and addressing challenges in astrophysical simulations.
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1 Lesons
46 minutes
On-Demand
Free-Video
Inside Livermore Lab

Machine-Precision Neural Networks for Multiscale Dynamics

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Discover how multi-stage neural networks can achieve machine-precision accuracy in scientific predictions, addressing spectral bias and improving deep learning applications in multiscale physics problems.
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1 Lesons
1 hour 9 minutes
On-Demand
Free-Video
International Centre for Theoretical Sciences

Laboratory for Interdisciplinary Breakthrough Science - Hybrid

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Explore machine learning's impact on scientific challenges through an industry-academia consortium, fostering collaboration between TIFR centers and ML experts to tackle significant disciplinary problems.
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18 Lesons
1 hour 8 minutes
On-Demand
Free-Video
Fields Institute

Learning Port Hamiltonian Structures Using PINNs Architecture

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Explore innovative techniques for learning Port Hamiltonian structures using Physics-Informed Neural Networks, enhancing understanding of dynamical systems and machine learning applications.
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1 Lesons
30 minutes
On-Demand
Free-Video
NPTEL-NOC IITM

Physics Informed Neural Networks - BC Incorporation

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Explore Physics Informed Neural Networks and learn techniques for incorporating boundary conditions in these advanced machine learning models.
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1 Lesons
18 minutes
On-Demand
Free-Video
NPTEL-NOC IITM

Code Walkthrough for PINNs in Burgers Equation

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Explore Physics-Informed Neural Networks (PINNs) applied to the Burgers equation through a detailed code walkthrough.
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1 Lesons
23 minutes
On-Demand
Free-Video
NPTEL-NOC IITM

Physics Informed Neural Networks - Introduction

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Explore the fundamentals of Physics Informed Neural Networks in this concise introduction.
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1 Lesons
22 minutes
On-Demand
Free-Video
SAIConference

Foundational AI 3.0: Unveiling the Future of AI Systems

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Explore AI's evolution from models to systems, focusing on dynamic environments and Foundational Causal Models. Gain insights into the future of AI in robotics, VR/AR, and healthcare.
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1 Lesons
28 minutes
On-Demand
Free-Video
DataLearning@ICL

WarpPINN: Cine-MR Image Registration with Physics-Informed Neural Networks

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Explore WarpPINN, a physics-informed neural network for cardiac image registration. Learn how it quantifies local heart deformations, improving heart failure diagnosis through advanced strain estimation techniques.
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1 Lesons
58 minutes
On-Demand
Free-Video
DataLearning@ICL

Neuromancer: Differentiable Programming Library for Data-driven Modeling and Control

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Explore NeuroMANCER, an open-source library for integrating machine learning with scientific computing, solving optimization problems, and creating differentiable models with physics-based constraints.
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1 Lesons
59 minutes
On-Demand
Free-Video
Inside Livermore Lab

GPT-PINN and TGPT-PINN: Advanced Physics-Informed Neural Networks for Parametric PDEs

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Explore GPT-PINN and TGPT-PINN for efficient parametric PDE solutions. Learn meta-learning techniques to reduce training time and network complexity while maintaining accuracy across parameter domains.
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1 Lesons
59 minutes
On-Demand
Free-Video
NPTEL-NOC IITM

PINNs for Inverse Problems in Scientific Computing

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Explore Physics-Informed Neural Networks (PINNs) and their application in solving inverse problems in scientific computing and engineering.
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1 Lesons
30 minutes
On-Demand
Free-Video
DataLearning@ICL

Physics-Informed Neural Networks in Medicine

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Explore physics-informed neural networks' applications in medicine, focusing on innovative technologies combining data assimilation and machine learning.
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1 Lesons
57 minutes
On-Demand
Free-Video
Alan Turing Institute

NeuroMANCER - Differentiable Programming Library for Data-driven Modeling and Control

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Explore NeuroMANCER: an open-source library for integrating machine learning with scientific computing, focusing on parametric optimization, system identification, and optimal control.
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1 Lesons
1 hour
On-Demand
Free-Video
Alan Turing Institute

PirateNets - Physics-Informed Deep Learning with Residual Adaptive Networks

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Explore PirateNets: a novel deep learning architecture for solving PDE-governed problems, offering improved stability and efficiency over traditional physics-informed neural networks.
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1 Lesons
1 hour 3 minutes
On-Demand
Free-Video
Alan Turing Institute

Kalman-Bucy Informed Neural Networks for System Identification

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Combining physics-informed neural networks and Kalman filters to identify parameters in continuous-time systems with noisy measurements, improving model precision for complex systems.
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1 Lesons
1 hour 1 minute
On-Demand
Free-Video
Inside Livermore Lab

Competitive Physics Informed Networks - Overcoming Limitations in PDE Solutions

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Explore competitive physics-informed neural networks for solving PDEs with unprecedented accuracy. Learn about adversarial approaches and zero-sum games to achieve single-precision accuracy in numerical simulations.
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15 Lesons
1 hour 6 minutes
On-Demand
Free-Video
Inside Livermore Lab

Scientific Machine Learning through the Lens of Physics-Informed Neural Networks

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Explore physics-informed neural networks (PINNs) as an alternative to traditional scientific computation, addressing limitations and showcasing applications in solving complex physical problems.
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1 Lesons
1 hour 3 minutes
On-Demand
Free-Video
Inside Livermore Lab

Physics Informed Machine Learning through Symbolic Regression

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Explore symbolic regression for identifying PDE models from scarce, noisy data. Compare with Physics-Informed Neural Networks and discuss applications in fault detection and system health prognostics.
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1 Lesons
1 hour 9 minutes
On-Demand
Free-Video
Inside Livermore Lab

Neural Differentiable Physics: Unifying Numerical PDEs and Deep Learning for Data-Augmented Computational Physics

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Explore Neural Differentiable Physics, unifying numerical PDEs and deep learning for enhanced computational modeling of complex physical systems. Learn innovative SciML approaches integrating physics principles with AI.
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1 Lesons
1 hour 28 minutes
On-Demand
Free-Video