Math, code, concepts: A third road to deep learning
Not everybody who wants to get into deep learning has a strong background in math or programming. This post elaborates on a concepts-driven, abstracti…
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Audio classification with Keras: Looking closer at the non-deep learning parts
Sometimes, deep learning is seen - and welcomed - as a way to avoid laborious preprocessing of data. However, there are cases where preprocessing of s…
Discrete Representation Learning with VQ-VAE and TensorFlow Probability
Mostly when thinking of Variational Autoencoders (VAEs), we picture the prior as an isotropic Gaussian. But this is by no means a necessity. The Vecto…
Getting started with TensorFlow Probability from R
TensorFlow Probability offers a vast range of functionality ranging from distributions over probabilistic network layers to probabilistic inference. I…
Concepts in object detection
As shown in a previous post, naming and locating a single object in an image is a task that may be approached in a straightforward way. This is not th…
Entity embeddings for fun and profit
Embedding layers are not just useful when working with language data. As "entity embeddings", they've recently become famous for applications on tabul…
You sure? A Bayesian approach to obtaining uncertainty estimates from neural networks
In deep learning, there is no obvious way of obtaining uncertainty estimates. In 2016, Gal and Ghahramani proposed a method that is both theoretically…
Naming and locating objects in images
Object detection (the act of classifying and localizing multiple objects in a scene) is one of the more difficult, but very relevant in practice deep …
Representation learning with MMD-VAE
Like GANs, variational autoencoders (VAEs) are often used to generate images. However, VAEs add an additional promise: namely, to model an underlying …
Winner takes all: A look at activations and cost functions
Why do we use the activations we use, and how do they relate to the cost functions they tend to co-appear with? In this post we provide a conceptual i…
