Social And Emotional Learning Courses

Inside Livermore Lab

Multi-fidelity Linear Regression for Scientific Machine Learning from Scarce Data

Explore multi-fidelity linear regression for scientific machine learning, addressing data scarcity challenges in complex engineering systems through innovative training approaches.

• YouTube
• 1 hour
• Self-Paced
• Free Video

Inside Livermore Lab

Learning Paradigms for Neural Networks: The Locally Backpropagated Forward-Forward Algorithm

Explore innovative neural network training methods combining backpropagation and forward-forward algorithms to address limitations in complex, physics-related AI applications.

• YouTube
• 57 minutes
• Self-Paced
• Free Video

Inside Livermore Lab

Integrating Cyber Security and Machine Learning for Applications in Transportation Systems

Explore integrating cybersecurity and machine learning in transportation systems. Learn about challenges, research, and innovative solutions for securing Internet of Transportation and Intelligent Transportation Systems.

• YouTube
• 51 minutes
• Self-Paced
• Free Video

Inside Livermore Lab

Vertical Reasoning Enhanced Learning, Generation and Scientific Discovery

Explore vertical reasoning's impact on AI, enhancing image generation, symbolic regression, and PDE learning. Discover innovative approaches to integrating reasoning and learning for advanced AI applications.

• YouTube
• 1 hour 9 minutes
• Self-Paced
• Free Video

Inside Livermore Lab

Physics Informed Machine Learning through Symbolic Regression

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.

• YouTube
• 1 hour 9 minutes
• Self-Paced
• Free Video

Inside Livermore Lab

Towards Third Wave AI: Interpretable, Robust Trustworthy Machine Learning

Explore new theories and algorithms for complex dynamical systems, creating trustworthy AI for real-time prediction and national security applications. Learn about innovative neural networks and physics-integrated models.

• YouTube
• 49 minutes
• Self-Paced
• Free Video

Inside Livermore Lab

DeepParticle: Learning Invariant Measure by Deep Neural Network Minimizing Wasserstein Distance

Explore DeepParticle: an integrated approach combining deep learning, optimal transport, and interacting particles to solve high-dimensional PDEs, demonstrated through Fisher-Kolmogorov-Petrovsky-Piskunov front speeds in incompressible flows.

• YouTube
• 1 hour
• Self-Paced
• Free Video

Inside Livermore Lab

Structure-Preserving Learning of High-Dimensional Lagrangian and Hamiltonian Systems

Explore structure-preserving learning for high-dimensional Lagrangian and Hamiltonian systems, focusing on reduced-order models in mechanics, robotics, and wave propagation for enhanced stability and predictive accuracy.

• YouTube
• 1 hour 4 minutes
• Self-Paced
• Free Video

Inside Livermore Lab

Elliptic PDE Learning: Provably Data-Efficient Techniques

Explore data-efficient PDE learning techniques, combining deep learning with physics and mathematics to discover properties of unknown physical systems from limited experimental data.

• YouTube
• 59 minutes
• Self-Paced
• Free Video

Inside Livermore Lab

Generalizing Scientific Machine Learning and Differentiable Simulation Beyond Continuous Models

Explore generalizing scientific machine learning beyond continuous models, covering differentiable simulation for chaotic systems, stochastic processes, and inverse problems in advanced scientific computing.

• YouTube
• 58 minutes
• Self-Paced
• Free Video

Inside Livermore Lab

Challenges and Opportunities for Integrating Physics-Knowledge in Machine Learning Strategies

Explore integrating physics knowledge into machine learning algorithms for improved generalization and physics-consistent predictions. Examine biases and strategies through a friction identification case study.

• YouTube
• 1 hour 10 minutes
• Self-Paced
• Free Video

Inside Livermore Lab

Fokker-Planck-Inverse Reinforcement Learning

Explore Fokker-Planck-Inverse Reinforcement Learning for revealing agent behavior rationale. Learn about a novel physics-aware algorithm inferring transition and reward functions from observed trajectories.

• YouTube
• 1 hour 5 minutes
• Self-Paced
• Free Video

Inside Livermore Lab

Reduced Order Modeling and Inverse Design of Flexible Structures by Machine Learning

Explore machine learning applications in structural mechanics, focusing on reduced-order modeling for dynamic simulations and inverse design of shape-morphing structures using neural networks and active learning.

• YouTube
• 1 hour 3 minutes
• Self-Paced
• Free Video

Inside Livermore Lab

Tensor Factorization for Biomedical Representation Learning

Explore tensor factorization for biomedical representation learning, addressing challenges in healthcare data and improving predictive power for various downstream tasks.

• YouTube
• 1 hour 1 minute
• Self-Paced
• Free Video

Inside Livermore Lab

DDPS - A Flexible and Generalizable XAI Framework for Scientific Deep Learning

Explore a flexible XAI framework for scientific deep learning, enhancing interpretability and generalization in physics-based modeling through integral equations and sparse regression techniques.

• YouTube
• 53 minutes
• Self-Paced
• Free Video