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cs.CV2023
Hacking Generative Models with Differentiable Network Bending
Giacomo Aldegheri, Alina Rogalska, Ahmed Youssef +1
In this work, we propose a method to 'hack' generative models, pushing their outputs away from the original training distribution towards a new objective. We inject a small-scale t…
cs.CV2021
Category-orthogonal object features guide information processing in recurrent neural networks trained for object categorization
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 a…