Heath–Jarrow–Morton framework | Financial models | Mathematical finance
In mathematical finance, the Cheyette Model is a quasi-Gaussian, quadratic volatility model of interest rates intended to overcome certain limitations of the Heath-Jarrow-Morton framework. By imposing a special time dependent structure on the forward rate volatility function, the Cheyette approach allows for dynamics which are Markovian, in contrast to the general HJM model.This in turn allows the application of standard econometric valuation concepts. (Wikipedia).
Journées Hénon - 20/21 - André Brahic
Michel Hénon : un modèle pour nous tous
From playlist Michel Hénon Memoriam
How was it Made? Jacquard weaving
From playlist Engineering
My first "E" video!!!! Music ("Keep Calmed, Stay Relaxed") by JamieMo Copyright - Jamie Mo
From playlist BAGUETTE
Un tour sportif à travers l'expérience CMS, ses buts, et un zèste de sa physique.
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http://www.greenpowerscience.com/ DEMONSTRATION MODEL OF A FRESNEL LENS PERFECT FOR FAST DEMOS
From playlist FRESNEL LENS
From playlist the absolute best of stereolab
Nikolaus Kriegskorte - Controversial stimuli: experiments to adjudicate computational hypotheses
Recorded 13 January 2023. Nikolaus Kriegeskorte of Columbia University presents "Controversial stimuli: Optimizing experiments to adjudicate among computational hypotheses" at IPAM's Explainable AI for the Sciences: Towards Novel Insights Workshop. Learn more online at: http://www.ipam.ucl
From playlist 2023 Explainable AI for the Sciences: Towards Novel Insights
Using & Expanding the NLP Models Hub 1 | Webinar
Spark NLP and Spark OCR Free Trials are available here: https://www.johnsnowlabs.com/spark-nlp-try-free/ The NLP Models Hub which powers the Spark NLP and NLU libraries takes a different approach than the hubs of other libraries like TensorFlow, PyTorch, and Hugging Face. While it also pr
From playlist AI & NLP Webinars
Learn about HEV modeling and simulation. In this video, you will: - Learn about different methods for creating HEV component models. - See how Powertrain Blockset™ and Simscape™ tools can be used for HEV modeling. - Learn best practices for getting started and creating new plant models.
From playlist Hybrid Electric Vehicles
DDPS | Learning hierarchies of reduced-dimension and context-aware models for Monte Carlo sampling
In this DDPS Seminar Series talk from Sept. 2, 2021, University of Texas at Austin postdoctoral fellow Ionut-Gabriel Farcas discusses hierarchies of reduced-dimension and context-aware low-fidelity models for multi-fidelity Monte Carlo sampling. Description: In traditional model reduction
From playlist Data-driven Physical Simulations (DDPS) Seminar Series
This is Lecture 14 of the CSE519 (Data Science) course taught by Professor Steven Skiena [http://www.cs.stonybrook.edu/~skiena/] at Stony Brook University in 2016. The lecture slides are available at: http://www.cs.stonybrook.edu/~skiena/519 More information may be found here: http://www
From playlist CSE519 - Data Science Fall 2016
Stanford CS330: Deep Multi-task & Meta Learning I 2021 I Lecture 15
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
DeepMind x UCL | Deep Learning Lectures | 11/12 | Modern Latent Variable Models
This lecture, by DeepMind Research Scientist Andriy Mnih, explores latent variable models, a powerful and flexible framework for generative modelling. After introducing this framework along with the concept of inference, which is central to it, Andriy focuses on two types of modern latent
From playlist Learning resources
Introduction to System Modeling
This video gives an overview of system modeling and how to make use of the simulation engine and built-in models that are integrated in Wolfram Language 11.3. The Wolfram SystemModeler Model Center is shown along with how to seamlessly move back and forth between it and a Wolfram Language
From playlist Introduction to Model Analytics with SystemModeler and the Wolfram Language
Stanford Seminar - Persistent and Unforgeable Watermarks for DeepNeural Networks
Huiying Li University of Chicago Emily Wegner University of Chicago October 30, 2019 As deep learning classifiers continue to mature, model providers with sufficient data and computation resources are exploring approaches to monetize the development of increasingly powerful models. Licen
From playlist Stanford EE380-Colloquium on Computer Systems - Seminar Series
Chapter 4 live sessions with Omar
This is a recording of the twitch session on July 7th 2021. Chapter 4 of the course: https://huggingface.co/course/chapter4 Have a question? Checkout the forums: https://discuss.huggingface.co/c/course/20 Subscribe to our newsletter: https://huggingface.curated.co/
From playlist Hugging Face Course: Live Sessions Recordings