A01 An introduction to a series on space medicine
A new series on space medicine.
From playlist Space Medicine
Build a scale model of the solar system to understand just how far the planets are from the Earth. License: Creative Commons BY-NC-SA More information at http://k12videos.mit.edu/terms-conditions
From playlist Measurement
What is a metric space? An example
This is a basic introduction to the idea of a metric space. I introduce the idea of a metric and a metric space framed within the context of R^n. I show that a particular distance function satisfies the conditions of being a metric.
From playlist Mathematical analysis and applications
After our introduction to matrices and vectors and our first deeper dive into matrices, it is time for us to start the deeper dive into vectors. Vector spaces can be vectors, matrices, and even function. In this video I talk about vector spaces, subspaces, and the porperties of vector sp
From playlist Introducing linear algebra
Interstellar flight: 10 Hard Facts
We can build powerful rockets able to carry people and machines into orbit, or even vault them to the moon. But our fastest spacecraft don't hold a candle to the distances that define Interstellar Flight. So what's on the drawing boards? What futuristic designs and fuel options promise to
From playlist Spaceten
What exactly is space? Brian Greene explains what the "stuff" around us is. Subscribe to our YouTube Channel for all the latest from World Science U. Visit our Website: http://www.worldscienceu.com/ Like us on Facebook: https://www.facebook.com/worldscienceu Follow us on Twitter: https:
From playlist Science Unplugged: Physics
NASA's newest X-ray telescope will have a lengthy structure that unfolds in space, allowing it to see high-energy objects like feeding black holes.
From playlist NuSTAR
From playlist Open Q&A
Sergey Melikhov, Steklov Math Institute (Moscow) Title: Fine Shape Abstract: A shape theory is something which is supposed to agree with homotopy theory on polyhedra and to treat more general spaces by looking at their polyhedral approximations. Or if you prefer, it is something which is s
From playlist 39th Annual Geometric Topology Workshop (Online), June 6-8, 2022
George Booth - A rigorous framework for embedding realistic interacting quantum systems - IPAM UCLA
Recorded 01 April 2022. George Booth of King's College London presents "A rigorous framework for embedding realistic interacting quantum systems" at IPAM's Multiscale Approaches in Quantum Mechanics Workshop. Abstract: We will discuss a recent reformulation of quantum embedding suitable fo
From playlist 2022 Multiscale Approaches in Quantum Mechanics Workshop
Stanford CS330: Deep Multi-task & Meta Learning I 2021 I Lecture 10
For more information about Stanford's Artificial Intelligence professional and graduate programs visit: https://stanford.io/ai To follow along with the course, visit: http://cs330.stanford.edu/fall2021/index.html To view all online courses and programs offered by Stanford, visit: http:/
From playlist Stanford CS330: Deep Multi-Task & Meta Learning I Autumn 2021I Professor Chelsea Finn
DDPS | Model reduction with adaptive enrichment for large scale PDE constrained optimization
Talk Abstract Projection based model order reduction has become a mature technique for simulation of large classes of parameterized systems. However, several challenges remain for problems where the solution manifold of the parameterized system cannot be well approximated by linear subspa
From playlist Data-driven Physical Simulations (DDPS) Seminar Series
An introduction to what will be on discussion in this lecture series on the appendix.
From playlist Acute Care Surgery
Stanford CS330: Multi-Task and Meta-Learning, 2019 | Lecture 8 - Model-Based Reinforcement Learning
For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit: https://stanford.io/ai Assistant Professor Chelsea Finn, Stanford University http://cs330.stanford.edu/
From playlist Stanford CS330: Deep Multi-Task and Meta Learning
Dynamical Reduction in General Relativistic Contexts by Daniel Sudarsky
21 November 2016 to 10 December 2016 VENUE Ramanujan Lecture Hall, ICTS Bangalore Quantum Theory has passed all experimental tests, with impressive accuracy. It applies to light and matter from the smallest scales so far explored, up to the mesoscopic scale. It is also a necessary ingredie
From playlist Fundamental Problems of Quantum Physics
A simple Qubit Regularization Scheme for SU(N) Lattice Gauge Theories by Shailesh Chandrasekharan
PROGRAM NONPERTURBATIVE AND NUMERICAL APPROACHES TO QUANTUM GRAVITY, STRING THEORY AND HOLOGRAPHY (HYBRID) ORGANIZERS: David Berenstein (University of California, Santa Barbara, USA), Simon Catterall (Syracuse University, USA), Masanori Hanada (University of Surrey, UK), Anosh Joseph (II
From playlist NUMSTRING 2022
HLCS | Interpretable and Explainable Data-Driven Methods for Physical Simulations
Description: A data-driven model can be built to accurately accelerate computationally expensive physical simulations, which is essential in multi-query problems, such as uncertainty quantification, design optimization, optimal control, and inverse problems. It is important to build interp
From playlist Hartree–Livermore Computational Science (HLCS)
From graph limits to higher order Fourier analysis – Balázs Szegedy – ICM2018
Combinatorics Invited Lecture 13.8 From graph limits to higher order Fourier analysis Balázs Szegedy Abstract: The so-called graph limit theory is an emerging diverse subject at the meeting point of many different areas of mathematics. It enables us to view finite graphs as approximation
From playlist Combinatorics
ARES: Aerial Regional-Scale Environmental Survey of Mars
Compilation video of the ARES Mars Eagle high altitude drop test including scenes of balloon inflation, airplane prep, balloon launch, and tail camera view of model deployment and pull-up maneuver.
From playlist Mars Aircraft
Stanford CS330: Multi-Task and Meta-Learning, 2019 | Lecture 4 - Non-Parametric Meta-Learners
For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit: https://stanford.io/ai Assistant Professor Chelsea Finn, Stanford University http://cs330.stanford.edu/
From playlist Stanford CS330: Deep Multi-Task and Meta Learning