Manal Helal's Journal Club session where she will talk about a paper "miRe2e: A Full End-to-End Deep Model Based on Transformers for Prediction of Pre-miRNAs"
Tag: neural networks
Learning To Count Everything
Minghua Zheng's Journal Club session where he will talk about a paper "Learning To Count Everything"
Synchronization through Uncorrelated Noise in Excitatory-Inhibitory Networks
Christoph Metzner's Journal Club session where he will talk about a paper "Synchronization through Uncorrelated Noise in Excitatory-Inhibitory Networks"
Learning Compositional Sequences with Multiple Time Scales through a Hierarchical Network of Spiking Neurons
Muhammad Yaqoob's Journal Club session where he will talk about a paper "Learning Compositional Sequences with Multiple Time Scales through a Hierarchical Network of Spiking Neurons"
Spatiotemporal network coding of physiological mossy fiber inputs by the cerebellar granular layer
Ohki Katakura's journal club session where he will talk about the paper "Spatiotemporal network coding of physiological mossy fiber inputs by the cerebellar granular layer".
Modelling nicotine addiction
Reinoud Maex's journal club session, where he will summerise the work he did in Paris, which was sponsored by Targacept: a pharmaceutical company which specialised in nicotinic compounds.
The power of deep networks and learning
Shabnam Kadir's journal club session, where she will present the papers "The power of deeper networks for expressing natural functions (David Rolnick and Max Tegmark, 2018)" and "Why does deep and cheap learning work so well? (Henry W. Lin, Max Tegmark and David Rolnick, 2017)".
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PCA synaptic plasticity Associative memory Purkinje cell computational neuroscience Neurons robotics computational modelling Dendritic computation Evolutionary algorithms Open position Neuronal Morphology Network connectivity Homoeostasis Neuromorphic hardware Computer Science Artificial intelligence Persistent homology olfaction cerebellum Structural plasticity machine learning neural networks Studentship Convolutional Neural Networks neuroscience Software development COVID-19 optimization Deep learning
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