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Capsule Network Performance with Autonomous Navigation
Thomas Molnar, Eugenio Culurciello
Capsule Networks (CapsNets) have been proposed as an alternative to Convolutional Neural Networks (CNNs). This paper showcases how CapsNets are more capable than CNNs for autonomou…
Continual Reinforcement Learning in 3D Non-stationary Environments
Vincenzo Lomonaco, Karan Desai, Eugenio Culurciello +1
High-dimensional always-changing environments constitute a hard challenge for current reinforcement learning techniques. Artificial agents, nowadays, are often trained off-line in…
Robust Convolutional Neural Networks under Adversarial Noise
Jonghoon Jin, Aysegul Dundar, Eugenio Culurciello
Recent studies have shown that Convolutional Neural Networks (CNNs) are vulnerable to a small perturbation of input called "adversarial examples". In this work, we propose a new fe…
Convolutional Clustering for Unsupervised Learning
Aysegul Dundar, Jonghoon Jin, Eugenio Culurciello
The task of labeling data for training deep neural networks is daunting and tedious, requiring millions of labels to achieve the current state-of-the-art results. Such reliance on…