Blind deconvolution

Linear Desface

Here we show a quick way to set up a face in desmos using domain and range restrictions along with sliders. @shaunteaches

From playlist desmos

Transformer - Part 8 - Decoder (3): Encoder-decoder self-attention

This is the third video about the transformer decoder and the final video introducing the transformer architecture. Here we mainly learn about the encoder-decoder multi-head self-attention layer, used to incorporate information from the encoder into the decoder. It should be noted that thi

From playlist A series of videos on the transformer

reaLD 3D glasses filter with a linear polarising filter

This is for a post on my blog: http://blog.stevemould.com

From playlist Everything in chronological order

SESSION 3 Q&A

From playlist VISUALISE : Visualization for Informal Science Education

Dynamic Random Access Memory (DRAM). Part 3: Binary Decoders

This is the third in a series of computer science videos is about the fundamental principles of Dynamic Random Access Memory, DRAM, and the essential concepts of DRAM operation. This video covers the role of the row address decoder and the workings of generic binary decoders. It also expl

From playlist Random Access Memory

Blind Deconvolution of galaxy survey images - Starck - Workshop 2 - CEB T3 2018

Jean-Luc Starck (CEA) / 24.10.2018 Blind Deconvolution of galaxy survey images ---------------------------------- Vous pouvez nous rejoindre sur les réseaux sociaux pour suivre nos actualités. Facebook : https://www.facebook.com/InstitutHenriPoincare/ Twitter : https://twitter.com/InHe

From playlist 2018 - T3 - Analytics, Inference, and Computation in Cosmology

Mario Figueiredo: ADMM in Imaging Inverse Problems: Some History and Recent Advances

Abstract: The alternating direction method of multipliers (ADMM) is an optimization tool of choice for several imaging inverse problems, namely due its flexibility, modularity, and efficiency. In this talk, I will begin by reviewing our earlier work on using ADMM to deal with classical pro

From playlist Analysis and its Applications

SESSION 4 Q&A

From playlist VISUALISE : Visualization for Informal Science Education

Gabriel Peyré: Exact Support Recovery for Sparse Spikes Deconvolution

Gabriel Peyré: Exact Support Recovery for Sparse Spikes Deconvolution Abstract: In this talk, I study sparse spikes deconvolution over the space of measures, following several recent works (see for instance [2,3]). For non-degenerate sums of Diracs, we show that, when the signal-to-noise

From playlist HIM Lectures: Trimester Program "Mathematics of Signal Processing"

Planetary Imaging

To learn more about Wolfram Technology Conference, please visit: https://www.wolfram.com/events/technology-conference/ Speaker: Tom Sherlock Wolfram developers and colleagues discussed the latest in innovative technologies for cloud computing, interactive deployment, mobile devices, and

From playlist Wolfram Technology Conference 2018

Stanley Osher - Variational Methods for Computational Microscopy - IPAM at UCLA

Recorded 14 September 2022. Stanley Osher of the University of California, Los Angeles, presents "Variational Methods for Computational Microscopy" at IPAM's Computational Microscopy Tutorials. Learn more online at: http://www.ipam.ucla.edu/programs/workshops/computational-microscopy-tutor

From playlist Tutorials: Computational Microscopy 2022

Twelfth Imaging & Inverse Problems (IMAGINE) OneWorld SIAM-IS Virtual Seminar Series Talk

Date: Wednesday, February 3, 2021, 10:00am EDT Speaker: Laurent Demanet, Massachusetts Institute of Technology Title: Imaging from deepfake data Abstract: Neural networks might have an interesting and surprising role to play in the context of imaging/inversion from sensor data and physi

From playlist Imaging & Inverse Problems (IMAGINE) OneWorld SIAM-IS Virtual Seminar Series

Optical Magnification Explained

https://www.patreon.com/edmundsj If you want to see more of these videos, or would like to say thanks for this one, the best way you can do that is by becoming a patron - see the link above :). And a huge thank you to all my existing patrons - you make these videos possible. In this video

From playlist Geometric Optics

Structured Regularization Summer School - C. Fernandez-Granda - 20/06/2017

Carlos Fernandez-Granda (NYU): A sampling theorem for robust deconvolution Abstract: In the 70s and 80s geophysicists proposed using l1-norm regularization for deconvolution problem in the context of reflection seismology. Since then such methods have had a great impact in high-dimensiona

From playlist Structured Regularization Summer School - 19-22/06/2017

Hologram Project!!!

This video is used for Hologram technology, just make the hologram device at home with a very simple way, I'll put a video of how to make the Hologram device. Enjoy!

From playlist OPTICS

CS231n Lecture 13 - Segmentation, soft attention, spatial transformers

Segmentation Soft attention models Spatial transformer networks

From playlist CS231N - Convolutional Neural Networks

7 AMAZING OPTICS EXPERIMENTS (science experiments)

Physics (la physique)

From playlist OPTICS

Stanford CS230: Deep Learning | Autumn 2018 | Lecture 7 - Interpretability of Neural Network

Andrew Ng, Adjunct Professor & Kian Katanforoosh, Lecturer - Stanford University http://onlinehub.stanford.edu/ Andrew Ng Adjunct Professor, Computer Science Kian Katanforoosh Lecturer, Computer Science To follow along with the course schedule and syllabus, visit: http://cs230.stanfo

From playlist Stanford CS230: Deep Learning | Autumn 2018

Transformer - Part 6 - Decoder (1): testing and training

This is the first out of three videos about the transformer decoder. In this video, we focus on describing how the decoder is used during testing and training since this is helpful in order to understand how the decoder is constructed The video is part of a series of videos on the transfo

From playlist A series of videos on the transformer

Inaugural Imaging & Inverse Problems (IMAGINE) OneWorld SIAM-IS Virtual Seminar Series Talk

Date: Wednesday, October 14, 10:00am EDT Speaker: Michael Friedlander, University of British Columbia Title: Polar deconvolution of mixed signals Abstract: The signal demixing problem seeks to separate the superposition of multiple signals into its constituent components. We model the s

From playlist Imaging & Inverse Problems (IMAGINE) OneWorld SIAM-IS Virtual Seminar Series