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Introduction to GANS for Image and Data Generation (7.1)

GANs are a powerful neural network architecture composed of a discriminator and generator. We can teach a GAN to create synthetic data when given an example training set of actual data. In this video, we begin looking at NVIDIA StyleGAN3 and how to use the pretrained network provided by NVIDIA to generate realistic-looking synthetic faces. […]
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Applications of Deep Neural Networks Course Overview (1.1, Spring 2022)

Spring 2022 Version. Applications of deep neural networks is a course offered in a hybrid format by Washington University in St. Louis. This course introduces Keras deep neural networks and highlights applications that neural networks are particularly adept at handling compared to previous machine learning models. Deep learning is a group of exciting new technologies […]
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Two Minute Papers: New AI: Next Level Video Editing! 🤯

❤️ Train a neural network and track your experiments with Weights & Biases here: http://wandb.me/paperintro 📝 The paper “Layered Neural Atlases for Consistent Video Editing” is available here: https://layered-neural-atlases.github.io/ 🙏 We would like to thank our generous Patreon supporters who make Two Minute Papers possible: Aleksandr Mashrabov, Alex Balfanz, Alex Haro, Andrew Melnychuk, Angelos Evripiotis, […]
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04:57

Two Minute Papers: Photos Go In, Reality Comes Out…And Fast! 🌁

❤️ Check out Perceptilabs and sign up for a free demo here: https://www.perceptilabs.com/papers 📝 The paper “Plenoxels: Radiance Fields without Neural Networks” is available here: https://alexyu.net/plenoxels/ ❤️ Watch these videos in early access on our Patreon page or join us here on YouTube: – https://www.patreon.com/TwoMinutePapers – https://www.youtube.com/channel/UCbfYPyITQ-7l4upoX8nvctg/join 🙏 We would like to thank our generous […]
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03:19:44

061: Interpolation, Extrapolation and Linearisation (Prof. Yann LeCun, Dr. Randall Balestriero)

We are now sponsored by Weights and Biases! Please visit our sponsor link: http://wandb.me/MLST Yann LeCun thinks that it’s specious to say neural network models are interpolating because in high dimensions, everything is extrapolation. Recently Dr. Randall Bellestrerio, Dr. Jerome Pesente and prof. Yann LeCun released their paper learning in high dimensions always amounts to […]
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40:38

SingularityNET: Modeling COVID-19 Using Simulated Agents with Intelligence and Culture – Dr. Deborah Duong

➡️ COVID-19 Simulation Summit Playlist: https://www.youtube.com/playlist?list=PLAJnaovHtaFR5puHCN4W_4o8cgIHdawDb ——————————————— 👀 About the speaker Dr. Deborah Duong is Director or AI Development at Rejuve and Director of Network Analytics at Singularity Net. The focus of her research is Complex Adaptive Systems, on the boundary between AI and Computational Social Science. She wrote the world’s first Intelligent Agent Based […]
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Top Kaggle Solution for Fall 2021 Semester

In this video, one of my students from Washington University provides an overview of his winning solution for the Fall 2021 Kaggle Competition. Each semester I hold a Kaggle In-Class competition for my deep learning course. Hawoo Im’s LinkedIn Page https://www.linkedin.com/in/hawooim/ Code: Kaggle Competition: https://www.kaggle.com/c/applications-of-deep-learning-wustlfall-2021/overview T81-558: Applications of Deep Neural Networks T81-558:Applications of Deep Neural […]
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04:57

Two Minute Papers: NVIDIA’s New AI: Journey Into Virtual Reality!

❤️ Train a neural network and track your experiments with Weights & Biases here: http://wandb.me/paperintro 📝 The paper “Physics-based Human Motion Estimation and Synthesis from Videos” is available here: https://nv-tlabs.github.io/physics-pose-estimation-project-page/ 🙏 We would like to thank our generous Patreon supporters who make Two Minute Papers possible: Aleksandr Mashrabov, Alex Balfanz, Alex Haro, Andrew Melnychuk, Angelos […]
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Two Minute Papers: Visually Indicated Sounds | Two Minute Papers #79

The Scholarly Store is available here: https://shop.spreadshirt.net/TwoMinutePapers Using the power of deep learning, it is now possible to create a technique that looks at a silent video and synthesize appropriate sound effects for it. The usage is at the moment, limited to hitting these objects with a drumstick. Note: The authors seem to lean on […]
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04:48

Two Minute Papers: Estimating Matrix Rank With Neural Networks | Two Minute Papers #94

This tongue in cheek work is about identifying matrix ranks from images, plugging in a convolutional neural network where it is absolutely inaproppriate to use. The paper “Visually Identifying Rank” is available here: http://www.oneweirdkerneltrick.com/rank.pdf David Fouhey’s website is available here: http://www.cs.cmu.edu/~dfouhey/ The machine learning calculator is available here: http://armlessjohn404.github.io/calcuMLator/ The paper “Separable Subsurface Scattering” is […]
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03:29

Two Minute Papers: Training Deep Neural Networks With Dropout | Two Minute Papers #62

In this episode, we discuss the bane of many machine learning algorithms – overfitting. It is also explained why it is an undesirable way to learn and how to combat it via dropout. _____________________ The paper “Dropout: A Simple Way to Prevent Neural Networks from Overtting” is available here: https://www.cs.toronto.edu/~hinton/absps/JMLRdropout.pdf Andrej Karpathy’s autoencoder is available […]
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04:34

Two Minute Papers: Overfitting and Regularization For Deep Learning | Two Minute Papers #56

In this episode, we discuss the bane of many machine learning algorithms – overfitting. It is also explained why it is an undesirable way to learn and how to combat it via L1 and L2 regularization. _____________________________ The paper “Regression Shrinkage and Selection via the Lasso” is available here: http://statweb.stanford.edu/~tibs/lasso/lasso.pdf Andrej Karpathy’s excellent lecture notes […]
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03:18

Two Minute Papers: Semantic Scene Completion From One Depth Image | Two Minute Papers #147

The paper “Semantic Scene Completion from a Single Depth Image” is available here: http://sscnet.cs.princeton.edu/ Recommended for you: How Does Deep Learning Work? – https://www.youtube.com/watch?v=He4t7Zekob0 Artificial Neural Networks and Deep Learning – https://www.youtube.com/watch?v=rCWTOOgVXyE WE WOULD LIKE TO THANK OUR GENEROUS PATREON SUPPORTERS WHO MAKE TWO MINUTE PAPERS POSSIBLE: Andrew Melnychuk, Christian Lawson, Daniel John Benton, Dave […]
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07:21

Using Pretrained Neural Networks with Keras (6.3)

Keras allows you make use of advanced pretrained neural networks for computer vision. You can make use this training, or perhaps only use the structure of these advanced neural networks, and train for your own images. Code for This Video: https://github.com/jeffheaton/t81_558_deep_learning/blob/master/t81_558_class_06_3_resnet.ipynb Course Homepage: https://sites.wustl.edu/jeffheaton/t81-558/ Follow Me/Subscribe: https://www.youtube.com/user/HeatonResearch https://github.com/jeffheaton Tweets by jeffheaton Support Me on Patreon: […]