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pro vyhledávání: '"Echeveste, Rodrigo"'
Autor:
Ferrante, Enzo, Echeveste, Rodrigo
Recently, the research community of computerized medical imaging has started to discuss and address potential fairness issues that may emerge when developing and deploying AI systems for medical image analysis. This chapter covers some of the pressin
Externí odkaz:
http://arxiv.org/abs/2407.16953
Deep learning methods are increasingly becoming instrumental as modeling tools in computational neuroscience, employing optimality principles to build bridges between neural responses and perception or behavior. Developing models that adequately repr
Externí odkaz:
http://arxiv.org/abs/2404.15390
It has recently been shown that deep learning models for anatomical segmentation in medical images can exhibit biases against certain sub-populations defined in terms of protected attributes like sex or ethnicity. In this context, auditing fairness o
Externí odkaz:
http://arxiv.org/abs/2309.00451
In recent years the development of artificial intelligence (AI) systems for automated medical image analysis has gained enormous momentum. At the same time, a large body of work has shown that AI systems can systematically and unfairly discriminate a
Externí odkaz:
http://arxiv.org/abs/2305.05101
In real-life applications, machine learning models often face scenarios where there is a change in data distribution between training and test domains. When the aim is to make predictions on distributions different from those seen at training, we inc
Externí odkaz:
http://arxiv.org/abs/2108.01621
Theories for autism spectrum disorder (ASD) have been formulated at different levels: ranging from physiological observations to perceptual and behavioral descriptions. Understanding the physiological underpinnings of perceptual traits in ASD remains
Externí odkaz:
http://arxiv.org/abs/2106.04366
Asymptotic scaling properties of the posterior mean and variance in the Gaussian scale mixture model
The Gaussian scale mixture model (GSM) is a simple yet powerful probabilistic generative model of natural image patches. In line with the well-established idea that sensory processing is adapted to the statistics of the natural environment, the GSM h
Externí odkaz:
http://arxiv.org/abs/1706.00925
Autor:
Echeveste, Rodrigo, Gros, Claudius
Publikováno v:
Frontiers in Computational Neuroscience, 10:98, 2016
The study of balanced networks of excitatory and inhibitory neurons has led to several open questions. On the one hand it is yet unclear whether the asynchronous state observed in the brain is autonomously generated, or if it results from the interpl
Externí odkaz:
http://arxiv.org/abs/1609.06462
Autor:
Echeveste, Rodrigo, Gros, Claudius
Self-organization provides a framework for the study of systems in which complex patterns emerge from simple rules, without the guidance of external agents or fine tuning of parameters. Within this framework, one can formulate a guiding principle for
Externí odkaz:
http://arxiv.org/abs/1505.04010
Autor:
Echeveste, Rodrigo, Gros, Claudius
Publikováno v:
Neural Computation 2015, 27(3), 672-698
We present an effective model for timing-dependent synaptic plasticity (STDP) in terms of two interacting traces, corresponding to the fraction of activated NMDA receptors and the Ca2+ concentration in the dendritic spine of the postsynaptic neuron.
Externí odkaz:
http://arxiv.org/abs/1410.0557