s. These sub-experimental data sets are vertically concatenated to form a stacked analytic file. The goal is to est mate an average causal e↵ect by fitting DID or event study regressions to the stacked …

What is a stacked DID or stacked event study? A stacked DID or stacked event study is a way to analyze data from a staggered adoption design.

This procedure can be repeated indefinitely and create stacked autoencoder layers of arbitrary depth. It is been shown that each subsequent trained layer learns a better representation of the output of the …

This paper is organized as follows: Section 2.1 formally describes stacked generalization, including usage of indicator functions to transform the multi- class problem into several regressionproblems …

A complete pipeline for 3D counting of overlapping, stacked objects, a novel and challenging computer vision task not previously addressed in the literature. A network designed to infer the occupancy …

We demonstrate that stacking a 2-Layer RNN provides better results on image captioning tasks than both a Vanilla LSTM and a Vanilla RNN.

In this paper, we propose a novel generative model named Stacked Generative Adversarial Networks (SGAN), which is trained to invert the hierarchical representations of a bottom-up discriminative …