torch: Just-in-time compilation (JIT) for R-less model deployment
Using the torch just-in-time (JIT) compiler, it is possible to query a model trained in R from a different language, provided that language can make u…
Tag: torch
Que haja luz: More light for torch!
Today, we're introducing luz, a high-level interface to torch that lets you train neural networks in a concise, declarative style. In some sense, it i…
torch for optimization
Torch is not just for deep learning. Its L-BFGS optimizer, complete with Strong-Wolfe line search, is a powerful tool in unconstrained as well as cons…
torch time series, final episode: Attention
We conclude our mini-series on time-series forecasting with torch by augmenting last time's sequence-to-sequence architecture with a technique both im…
torch time series, take three: Sequence-to-sequence prediction
In our overview of techniques for time-series forecasting, we move on to sequence-to-sequence models. Architectures in this family are commonly used i…
torch time series continued: A first go at multi-step prediction
We continue our exploration of time-series forecasting with torch, moving on to architectures designed for multi-step prediction. Here, we augment the…
Introductory time-series forecasting with torch
This post is an introduction to time-series forecasting with torch. Central topics are data input, and practical usage of RNNs (GRUs/LSTMs). Upcoming …
torch, tidymodels, and high-energy physics
Today we introduce tabnet, a torch implementation of "TabNet: Attentive Interpretable Tabular Learning" that is fully integrated with the tidymodels f…
Simple audio classification with torch
This article translates Daniel Falbel's post on "Simple Audio Classification" from TensorFlow/Keras to torch/torchaudio.
Brain image segmentation with torch
The need to segment images arises in various sciences and their applications, many of which are vital to human (and animal) life. In this introductory…
