Publications by Krzysztof Joachimiak
Flat indices for arrays in R/Rcpp
Although 3-dimensional arrays are not the most common object used among the R projects, which are dominated by data.frame-like objects. However, when we’re starting to work with deep learning, (e.g. using {keras}), we can run into such objects many times, especially in fields like time series forecasting or NLP. The question I’d like to answe...
1826 sym R (1058 sym/7 pcs) 2 img
Flat indices for arrays in R/Rcpp
Although 3-dimensional arrays are not the most common object used among the R projects, which are dominated by data.frame-like objects. However, when we’re starting to work with deep learning, (e.g. using {keras}), we can run into such objects many times, especially in fields like time series forecasting or NLP. The question I’d like to answe...
1824 sym R (1060 sym/7 pcs) 2 img
path.chain: Concise Structure for Chainable Paths
path.chain package provides an intuitive and easy-to-use system of nested objects, which represents different levels of some directory’s structure in the file system. It allows us to Look at the path.chain Sometimes one picture can say more, than a thousand words, and this is exactly the case. Motivation ———- I’ve been working on the M...
1753 sym R (1058 sym/5 pcs) 4 img
S4 vs vctrs library – A Double Dispatch Comparision Remake
Remake About two weeks ago, I published on my blog a comparision between two possible implementation of double-dispatch: S4-based and vctrs-based. It turned out, that in my trials vctrs performed better. However, two days later I’ve got a message from Lionel Henry via comment to my commit on GitHub. He suggested, that S4 got faster in the newes...
4606 sym R (7484 sym/21 pcs) 16 img
Time Series & torch #1 – Training a network to compute moving average
In the previous year, I published a post, which as I hoped, was the first tutorial of the series describing how to effectively use PyTorch in Time Series Forecasting. Recently, a new exciting R package was submitted on CRAN. This great news was officially announced on the RStudio AI Blog. Yes, you mean right – the R port of PyTorch – called s...
5544 sym R (7210 sym/12 pcs) 6 img
Conditional RNN in keras (R) to deal with static features
Conditional RNN is one of the possible solutions if we’d like to make use of static features in time series forecasting. For example, we want to build a model, which can handle multiple time series with many different characteristics. It can be a model for demand forecasting for multiple products or a unified model forecasting temperature in pl...
3336 sym R (12723 sym/12 pcs) 14 img 1 tbl