AIMC Topic: Creativity
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Bioinspired translation of classical music intoprotein structures using deep learning and molecular modeling.
Bioinspiration & biomimetics
Nov 26, 2021
Architected biomaterials, as well as sound and music, are constructed from small building blocks that are assembled across time- and length-scales. Here we present a novel deep learning-enabled integrated algorithmic workflow to merge the two concept...
Mediating artificial intelligence developments through negative and positive incentives.
PloS one
Jan 26, 2021
The field of Artificial Intelligence (AI) is going through a period of great expectations, introducing a certain level of anxiety in research, business and also policy. This anxiety is further energised by an AI race narrative that makes people belie...
Developing a neurally informed ontology of creativity measurement.
NeuroImage
Jul 16, 2020
A central challenge for creativity research-as for all areas of experimental psychology and cognitive neuroscience-is to establish a mapping between constructs and measures (i.e., identifying a set of tasks that best captures a set of creative abilit...
Classifying creativity: Applying machine learning techniques to divergent thinking EEG data.
NeuroImage
May 28, 2020
Prior research has shown that greater EEG alpha power (8-13 Hz) is characteristic of more creative individuals, and more creative task conditions. The present study investigated the potential for machine learning to classify more and less creative b...
Artificial Intelligence in Radiotherapy: A Philosophical Perspective.
Journal of medical imaging and radiation sciences
Oct 4, 2019
The increasing uptake of machine learning solutions for segmentation and planning leaves no doubt that artificial intelligence (AI) will soon be providing input into a range of radiotherapy procedures. Although this promises to deliver increased spee...
Infrastructural intelligence: Contemporary entanglements between neuroscience and AI.
Progress in brain research
Jul 31, 2017
In this chapter, I reflect on contemporary entanglements between artificial intelligence and the neurosciences by tracing the development of Google's recent DeepMind algorithms back to their roots in neuroscientific studies of episodic memory and ima...
Deep dreaming, aberrant salience and psychosis: Connecting the dots by artificial neural networks.
Schizophrenia research
Jan 24, 2017
Why some individuals, when presented with unstructured sensory inputs, develop altered perceptions not based in reality, is not well understood. Machine learning approaches can potentially help us understand how the brain normally interprets sensory ...
Novel plasticity rule can explain the development of sensorimotor intelligence.
Proceedings of the National Academy of Sciences of the United States of America
Oct 26, 2015
Grounding autonomous behavior in the nervous system is a fundamental challenge for neuroscience. In particular, self-organized behavioral development provides more questions than answers. Are there special functional units for curiosity, motivation, ...
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