Structural causal models offer a popular framework for exploring causal concepts. However, due to their limited expressiveness, structural models have difficulties coping with su...
In this paper, we present discrete-time, nonspatial, macroscopic models able to capture the dynamics of collective aggregation experiments using groups of embodied agents endowed ...
William Agassounon, Alcherio Martinoli, Kjerstin E...
Abstract. This paper presents a neural network tree regression system with dynamic optimization of input variable transformations and post-training optimization. The decision tree ...
Miroslaw Kordos, Marcin Blachnik, Tadeusz Wieczore...
In this paper, we propose a general framework for fusing bottom-up segmentation with top-down object behavior classification over an image sequence. This approach is beneficial fo...
The vast majority of work on skyline queries considers totally ordered domains, whereas in many applications some attributes are partially ordered, as for instance, domains of set ...