4 years ago
Deep Learning
Generating Text Summaries Using GPT-2 on PyTorch with Minimal Training
In this article I will discuss an efficient abstractive text summarization approach using GPT-2 on PyTorch with the CNN/Daily Mail dataset.
5 years ago
Attention Mechanisms in Computer Vision: CBAM
This post covers an in-depth analysis of the Convolution Block Attention Module (CBAM) with a short introduction to Visual Attention Mechanisms.
5 years ago
Fighting Coronavirus with AI, Part 2: Building a CT Scan COVID-19 Classifier Using PyTorch
Using PyTorch, we create a COVID-19 classifier that predicts whether a patient is suffering from coronavirus or not, using chest CT scans of different patients.
5 years ago
A Review of Popular Deep Learning Architectures: DenseNet, ResNeXt, MnasNet, and ShuffleNet v2
In this tutorial we will explore the four popular deep learning architectures for efficiently developing deep learning models.
By
Vihar Kurama
A Review of Popular Deep Learning Architectures: AlexNet, VGG16, and GoogleNet
Dive into a review of three foundational deep-learning architectures. Discover their key contributions, strengths, and how they paved the way for modern AI advancements.
By
Vihar Kurama
Turning Noise Into Signal: Using AI to Gain Context for Scientific Research
Josh Nicholson is the Co-Founder and CEO of scite (www.scite.ai), which is using deep learning to analyze the entirety of the scientific literature to better measure the veracity of scientific work.
5 years ago
