- Recreating Fingerprints using Convolutional Autoencoders - Mar 4, 2020.
The article gets you started working with fingerprints using Deep Learning.
- Top 10 AI, Machine Learning Research Articles to know - Jan 30, 2020.
We’ve seen many predictions for what new advances are expected in the field of AI and machine learning. Here, we review a “data set” based on what researchers were apparently studying at the turn of the decade to take a fresh glimpse into what might come to pass in 2020.
- Neural Networks 201: All About Autoencoders - Nov 21, 2019.
Autoencoders can be a very powerful tool for leveraging unlabeled data to solve a variety of problems, such as learning a "feature extractor" that helps build powerful classifiers, finding anomalies, or doing a Missing Value Imputation.
- Interpolation in Autoencoders via an Adversarial Regularizer - Mar 29, 2019.
Adversarially Constrained Autoencoder Interpolation (ACAI; Berthelot et al., 2018) is a regularization procedure that uses an adversarial strategy to create high-quality interpolations of the learned representations in autoencoders.
- Variational Autoencoders Explained in Detail - Nov 30, 2018.
We explain how to implement VAE - including simple to understand tensorflow code using MNIST and a cool trick of how you can generate an image of a digit conditioned on the digit.
- How GOAT Taught a Machine to Love Sneakers - Aug 7, 2018.
Embeddings are a fantastic tool to create reusable value with inherent properties similar to how humans interpret objects. GOAT uses deep learning to generate these for their entire sneaker catalogue.
- Deep Learning, The Curse of Dimensionality, and Autoencoders - Mar 12, 2015.
Autoencoders are an extremely exciting new approach to unsupervised learning and for many machine learning tasks they have already surpassed the decades of progress made by researchers handpicking features.
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