3.5k citations · 9.4k across the 45 of their papers we have counts for
3 papers · 1 filter
Resolving the paradox of evolvability with learning theory: How evolution learns to improve evolvability on rugged fitness landscapes
Loizos Kounios, Jeff Clune, Kostas Kouvaris +4
It has been hypothesized that one of the main reasons evolution has been able to produce such impressive adaptations is because it has improved its own ability to evolve -- "the ev…
Synthesizing the preferred inputs for neurons in neural networks via deep generator networks
Anh Nguyen, Alexey Dosovitskiy, Jason Yosinski +2
Deep neural networks (DNNs) have demonstrated state-of-the-art results on many pattern recognition tasks, especially vision classification problems. Understanding the inner working…
Multifaceted Feature Visualization: Uncovering the Different Types of Features Learned By Each Neuron in Deep Neural Networks
Anh Nguyen, Jason Yosinski, Jeff Clune
We can better understand deep neural networks by identifying which features each of their neurons have learned to detect. To do so, researchers have created Deep Visualization tech…