Hacking Generative Models with Differentiable Network Bending

1 code implementation • 7 Oct 2023 • Giacomo Aldegheri, Alina Rogalska, Ahmed Youssef, Eugenia Iofinova

In this work, we propose a method to 'hack' generative models, pushing their outputs away from the original training distribution towards a new objective.

Category-orthogonal object features guide information processing in recurrent neural networks trained for object categorization

1 code implementation • NeurIPS Workshop SVRHM 2021 • Sushrut Thorat, Giacomo Aldegheri, Tim C. Kietzmann

Recurrent neural networks (RNNs) have been shown to perform better than feedforward architectures in visual object categorization tasks, especially in challenging conditions such as cluttered images.

Object Object Categorization

Modulation of early visual processing alleviates capacity limits in solving multiple tasks

1 code implementation • 29 Jul 2019 • Sushrut Thorat, Giacomo Aldegheri, Marcel A. J. van Gerven, Marius V. Peelen

In daily life situations, we have to perform multiple tasks given a visual stimulus, which requires task-relevant information to be transmitted through our visual system.

object-detection Object Detection