11 citations · 28 across the 15 of their papers we have counts for
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stat.ML2021
Mill.jl and JsonGrinder.jl: automated differentiable feature extraction for learning from raw JSON data
Simon Mandlik, Matej Racinsky, Viliam Lisy +1
Learning from raw data input, thus limiting the need for manual feature engineering, is one of the key components of many successful applications of machine learning methods. While…
stat.ML2020★ 3 cited
Sum-Product-Transform Networks: Exploiting Symmetries using Invertible Transformations
Tomas Pevny, Vasek Smidl, Martin Trapp +2
In this work, we propose Sum-Product-Transform Networks (SPTN), an extension of sum-product networks that uses invertible transformations as additional internal nodes. The type and…
stat.ML2019★ 5 cited
Anomaly scores for generative models
Václav Šmídl, Jan Bím, Tomáš Pevný
Reconstruction error is a prevalent score used to identify anomalous samples when data are modeled by generative models, such as (variational) auto-encoders or generative adversari…