Fabio Anselmi
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Fabio Anselmi
Assistant Professor
Positions
- Assistant Professor
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Neuroscience
Baylor College of Medicine
Professional Statement
The investigation of learning as a computational process plays a fundamental role in machine learning and computational neuroscience where it is arguably considered to be the key for understanding intelligence. My current research focuses on computational aspects of learning in particular: * Development of biologically grounded machine learning algorithms for efficient computational methods with application to unsupervised learning and design of new plasticity rules in the brain cortex. * Sample efficient deep networks where the learned representations are adapted to priors in the data, in particular symmetries, through new regularization schemes. * Computational models for Grid cells in the hippocampus.Websites
Selected Publications
- Anselmi F. et al. "A computational model for grid maps in neural populations." JCN. 2020;48
- Anselmi et al. "Neurally plausible mechanisms for learning selective and invariant representations." JMN. 2020;
- Anselmi F. et al. "On Invariance and Selectivity in Representation Learning." Information and Inference. 2016;5
- Anselmi F. at al. "Symmetry regularization." Pattern Recognition. 2019;86
- J.Z. Leibo , Q. Liao , F. Anselmi, T. Poggio. "The invariance hypothesis implies domain-specific regions in visual cortex.." Plos Computational Biology. 2015;11
- Anselmi F. et al. "Unsupervised Learning of Invariant Representations.." Theoretical Computer Science. 2016;663
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