DDPS | Empowering Hybrid Twins from Physics-Informed Artificial Intelligence
Talk Abstract World is changing very rapidly. Today we do not sell aircraft engines, but hours of flight, we do not sell an electric drill but good quality holes, … and so on. We are nowadays more concerned by performances than by the products themselves. Thus, the new needs imply focusi
From playlist Data-driven Physical Simulations (DDPS) Seminar Series
Machine Learning for Computational Fluid Dynamics
Machine learning is rapidly becoming a core technology for scientific computing, with numerous opportunities to advance the field of computational fluid dynamics. This paper highlights some of the areas of highest potential impact, including to accelerate direct numerical simulations, to i
From playlist Data Driven Fluid Dynamics
Simulation: The Challenge for Data Science
While machine learning has recently had dramatic successes, there is a large class of problems that it will never be able to address on its own. To test a policy proposal, for example, often requires understanding a counterfactual scenario that has never existed in the past, and that may
From playlist Turing Seminars
Get started with real-time Data Streaming
Powered by Restream https://restream.io/ In the modern era, everyone expects their data the second it’s updated. Large corporations and Fortune 500 companies depend on this data to be able to predict consumer tastes or estimate where the forces of supply and demand are moving the market
From playlist Getting Started with Data Engineering
Data Modeling Tutorial | Data Modeling for Data Warehousing | Data Warehousing Tutorial | Edureka
***** Data Warehousing & BI Training: https://www.edureka.co/data-warehousing-and-bi ***** Data modeling is a process used to define and analyze data requirements needed to support the business processes within the scope of corresponding information systems in organizations. Therefore, th
From playlist Data Warehousing Tutorial Videos
If you are interested in learning more about this topic, please visit http://www.gcflearnfree.org/ to view the entire tutorial on our website. It includes instructional text, informational graphics, examples, and even interactives for you to practice and apply what you've learned.
From playlist Machine Learning
Bayesian optimisation for likelihood-free cosmological (...) - Leclercq - Workshop 2 - CEB T3 2018
Leclercq (Imperial College) / 22.10.2018 Bayesian optimisation for likelihood-free cosmological inference ---------------------------------- Vous pouvez nous rejoindre sur les réseaux sociaux pour suivre nos actualités. Facebook : https://www.facebook.com/InstitutHenriPoincare/ Twitter
From playlist 2018 - T3 - Analytics, Inference, and Computation in Cosmology
Reactive Systems use a high-performance software architecture. They are resilient under stress, and their reactive design allows them to scale elastically to meet demand. The reactive design approach allows the creation of more complex, more flexible systems and forms the basis for some of
From playlist Software Engineering
Continuous multi-fidelity optimization
This video is #8 in the Adaptive Experimentation series presented at the 18th IEEE Conference on eScience in Salt Lake City, UT (October 10-14, 2022). In this video, Sterling Baird @sterling-baird presents on continuous multifidelity optimization. Continuous multi-fidelity optimization is
From playlist Optimization tutorial
DDPS | Bayesian Optimization: Exploiting Machine Learning Models, Physics, & Throughput Experiments
We report new paradigms for Bayesian Optimization (BO) that enable the exploitation of large-scale machine learning models (e.g., neural nets), physical knowledge, and high-throughput experiments. Specifically, we present a paradigm that decomposes the performance function into a reference
From playlist Data-driven Physical Simulations (DDPS) Seminar Series
DDPS | Interpretable, Explainable and Non-Intrusive Uncertainty Propagation by Alice Cicirello
Title: Interpretable, Explainable and Non-Intrusive Uncertainty Propagation through Expensive-To-Evaluate models via ML-Optimization Description: Uncertainty models are used in conjunction with a computational model to compute the effects of uncertainties on a system performance. To supp
From playlist Data-driven Physical Simulations (DDPS) Seminar Series
Structured Regularization Summer School - C. Boyer - 22/06/2017
Claire Boyer (UPMC) Towards realistic compressed sensing Abstract: First, we will theoretically justify the applicability of compressed sensing (CS) in real-life applications. To do so, CS theorems compatible with physical acquisition constraints will be presented. These new results do n
From playlist Structured Regularization Summer School - 19-22/06/2017
Does 3D immersion enhance nursing students' pharmacology knowledge acquisition and satisfaction?
Presentation from The Campus Alliance for Advanced Visualization 2019 (CAAV19) held at Indiana University (IU) in Bloomington, Indiana. Abstract: Virtual reality has the unique potential to make healthcare education more readily available to students who have been previously marginalized
From playlist CAAV19 - The Campus Alliance for Advanced Visualization 2019
Data Visualization with D3, by Athena Braun
Data comes in many forms, but rarely is large spreadsheet the easiest way to glean information from it. Data visualization is a growing field in which researchers look for the best ways to show off their findings in digestible and even fun presentations. D3 is a powerful JavaScript library
From playlist CS50 Seminars 2018
Gabriele Vajente - Machine Learning and Gravitational Wave Detectors - IPAM at UCLA
Recorded 02 December 2021. Gabriele Vajente of the California Institute of Technology presents "Machine Learning and Gravitational Wave Detectors" at IPAM's Workshop IV: Big Data in Multi-Messenger Astrophysics. Abstract: The use of machine learning techniques in the analysis of the data p
From playlist Workshop: Big Data in Multi-Messenger Astrophysics
14 Data Analytics: Indicator Methods
Lecture on the use of indicators for spatial estimation and simulation.
From playlist Data Analytics and Geostatistics
Adding MCU Peripheral Modeling in Motor Control Using SoC Blockset
Learn about MCU peripherals modeling for motor control design and implementation on TI’s C2000™ microcontroller. - Embedded Systems | Developer Tech Showcase Playlist: https://www.youtube.com/playlist?list=PLn8PRpmsu08oYCg_v4ZZ6xmJlo3242Asj - Developer Tips & Tricks Videos: https://www.yo
From playlist Embedded Systems | Developer Tech Showcase
This video is #7 in the Adaptive Experimentation series presented at the 18th IEEE Conference on eScience in Salt Lake City, UT (October 10-14, 2022). In this video, Sterling Baird @sterling-baird presents on multiobjective optimization where a pareto front of non-dominated solutions can
From playlist Optimization tutorial
Lecture 9. Agent based modeling.
Data Science for Business. Lecture 9 slides: https://drive.google.com/file/d/1sw7OjZlAw61SC_cL7Tx9O2ct4kXlQcYn/view?usp=sharing
From playlist Data Science for Business, 2022
Andrew Ferguson: "Machine learning-enabled enhanced sampling in biomolecular simulation and..."
Machine Learning for Physics and the Physics of Learning Tutorials 2019 "Machine learning-enabled enhanced sampling in biomolecular simulation and data-driven design of self-assembling photonic crystals and optoelectonic π-conjugated oligopeptides" Andrew Ferguson, University of Chicago -
From playlist Machine Learning for Physics and the Physics of Learning 2019