How a Neural Network Sees a Cat
Article by Carlotta Castelluccio and Dmitry Soshnikov of Microsoft. As human beings, we know what a cat looks like. But what about neural networks? In this post, we reveal what a cat looks like inside a neural network brain, and also talk about adversarial attacks. Real... Read more
Portrait Depth API: Turning a Single Image into a 3D Photo with TensorFlow.js
Editor’s note: This article was reposted from the TensorFlow Blog with permission. To learn more about Web ML, be sure to check out Jason Mayes’ session at ODSC Europe 2022 titled “Next Generation Web Apps: Create a Machine Learning Powered Smart Cam in the Browser with... Read more
Practical Quantization in PyTorch
Quantization is a cheap and easy way to make your DNN run faster and with lower memory requirements. PyTorch offers a few different approaches to quantize your model. In this blog post, we’ll lay a (quick) foundation of quantization in deep learning, and then take a... Read more
Making Deep Learning Climate-Friendly
Deep learning is bringing many benefits to the world: solving the 50-year-old protein folding problem, detecting cancer, and improving the power grid. While there is so much that deep learning is powering, we also need to consider the costs. In the quest for more accurate and... Read more
Using Distillation to Protect Your Neural Networks
Distillation is a hot research area. For distillation, you first train a deep learning model, the teacher network, to solve your task. Then, you train a student network, which can be any model. While the teacher is trained on real data, the student is trained on the teacher’s outputs. It... Read more
AI Trained to Generate Novel Molecular Materials with a Generative Graph Grammar Model
Emerging technologies in the scientific community are helping researchers achieve more goals and make discoveries. Revolutionary tech such as artificial intelligence (AI) and machine learning (ML) have already disrupted various industries, from manufacturing to retail and beyond. ML has expedited the discovery process, especially for grad... Read more
Recurrent Neural Networks for Financial Time Series Prediction
Editor’s note: Nicole Königstein is a speaker for ODSC Europe 2022. Be sure to check out her talk, Dynamic and Context-Dependent Stock Price Prediction Using Attention Modules and News Sentiment, there to learn more about financial time series prediction! The use of neural networks is relatively... Read more
How to Determine the Optimal Learning Rate of Your Neural Network
One of the biggest challenges in building a deep learning model is choosing the right hyper-parameters. If the hyper-parameters aren’t ideal, the network may not be able to produce optimal results or development could be far more challenging. Perhaps the most difficult parameter to determine is... Read more
Google AI Introduces New DeepCTRL Method to Train Models
In early 2022, Google AI began releasing details about an exciting new method for training deep neural networks: DeepCTRL. Google’s AI team found a way to control rule strength and accuracy in deep neural networks, allowing for improvements in some crucial AI applications. DeepCTRL is more... Read more
Matrices and Their Connection to Graphs
Editor’s Note: Eric is a speaker for ODSC East 2022. Be sure to check out his talk, “Network Analysis Made Simple,” there! Graphs, also known as networks, are ubiquitous in our world. But did you know that graphs are also related to matrices and linear algebra?... Read more