6 citations · 7 across the 4 of their papers we have counts for
4 papers
Successes and Limitations of Object-centric Models at Compositional Generalisation
Milton L. Montero, Jeffrey S. Bowers, Gaurav Malhotra
In recent years, it has been shown empirically that standard disentangled latent variable models do not support robust compositional learning in the visual domain. Indeed, in spite…
MindSet: Vision. A toolbox for testing DNNs on key psychological experiments
Valerio Biscione, Milton L. Montero, Marin Dujmovic +9
Multiple benchmarks have been developed to assess the alignment between deep neural networks (DNNs) and human vision. In almost all cases these benchmarks are observational in the…
Lost in Latent Space: Disentangled Models and the Challenge of Combinatorial Generalisation
Milton L. Montero, Jeffrey S. Bowers, Rui Ponte Costa +2
Recent research has shown that generative models with highly disentangled representations fail to generalise to unseen combination of generative factor values. These findings contr…
Auto-Tag: Tagging-Data-By-Example in Data Lakes
Yeye He, Jie Song, Yue Wang +5
As data lakes become increasingly popular in large enterprises today, there is a growing need to tag or classify data assets (e.g., files and databases) in data lakes with addition…