2 code implementations • 8 Apr 2024 • Valerio Biscione, Dong Yin, Gaurav Malhotra, Marin Dujmovic, Milton L. Montero, Guillermo Puebla, Federico Adolfi, Rachel F. Heaton, John E. Hummel, Benjamin D. Evans, Karim Habashy, Jeffrey S. Bowers
Multiple benchmarks have been developed to assess the alignment between deep neural networks (DNNs) and human vision.
no code implementations • 5 Apr 2022 • Milton L. Montero, Jeffrey S. Bowers, Rui Ponte Costa, Casimir J. H. Ludwig, Gaurav Malhotra
Recent research has shown that generative models with highly disentangled representations fail to generalise to unseen combination of generative factor values.
no code implementations • 11 Dec 2021 • Yeye He, Jie Song, Yue Wang, Surajit Chaudhuri, Vishal Anil, Blake Lassiter, Yaron Goland, Gaurav Malhotra
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 additional metadata (e. g., semantic column-types), as the inferred metadata can enable a range of downstream applications like data governance (e. g., GDPR compliance), and dataset search.
1 code implementation • ICLR 2021 • Milton Llera Montero, Casimir JH Ludwig, Rui Ponte Costa, Gaurav Malhotra, Jeffrey Bowers
It is claimed that such representations should be able to capture the compositional structure of the world which can then be combined to produce novel representations.
no code implementations • ICLR 2019 • Gaurav Malhotra, Jeffrey Bowers
Convolutional neural networks (CNNs) were inspired by human vision and, in some settings, achieve a performance comparable to human object recognition.