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Romagnoni, Alberto
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1

Neuronal cable equations derived from the hydrodynamic moti..:

Forcella, Davide ; Romagnoni, Alberto ; Destexhe, Alain
Zeitschrift für angewandte Mathematik und Physik.  74 (2023)  3 - p. , 2023
Link: https://doi.org/10.1007/..
 
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2

A deep learning model to predict RNA-Seq expression of tumo..:

Schmauch, Benoît ; Romagnoni, Alberto ; Pronier, Elodie...
Nature Communications.  11 (2020)  1 - p. , 2020
Link: https://doi.org/10.1038/..
 
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3

State-dependent mean-field formalism to model different act..:

Capone, Cristiano ; di Volo, Matteo ; Romagnoni, Alberto..
Physical Review E.  100 (2019)  6 - p. , 2019
Link: https://doi.org/10.1103/..
 
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4

Comparative performances of machine learning methods for cl..:

Romagnoni, Alberto ; Jégou, Simon ; Van Steen, Kristel...
Scientific Reports.  9 (2019)  1 - p. , 2019
Link: https://doi.org/10.1038/..
 
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5

Pinwheel-dipole configuration in cat early visual cortex:

Ribot, Jérôme ; Romagnoni, Alberto ; Milleret, Chantal..
NeuroImage.  128 (2016)  - p. 63-73 , 2016
Link: https://doi.org/10.1016/..
 
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6

Parsimony, Exhaustivity and Balanced Detection in Neocortex:

Romagnoni, Alberto ; Ribot, Jérôme ; Bennequin, Daniel..
PLOS Computational Biology.  11 (2015)  11 - p. e1004623 , 2015
Link: https://doi.org/10.1371/..
 
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7

Extra U(1) as natural source of a monochromatic gamma ray l..:

Dudas, Emilian ; Mambrini, Yann ; Pokorski, Stefan.
Journal of High Energy Physics.  2012 (2012)  10 - p. , 2012
Link: https://doi.org/10.1007/..
 
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8

Neuronal cable equations derived from the hydrodynamic moti..:

Forcella, Davide ; Romagnoni, Alberto ; Destexhe, Alain
http://arxiv.org/abs/2201.04927.  , 2022
Link: http://arxiv.org/abs/220..
 
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9

Progressive alignment of inhibitory and excitatory delay ma..:

Romagnoni, Alberto ; Colonnese, Matthew ; Touboul, Jonathan.
info:eu-repo/semantics/altIdentifier/doi/10.1152/jn.00402.2019.  , 2020
Link: https://hal.science/hal-..
 
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10

Progressive alignment of inhibitory and excitatory delay ma..:

Romagnoni, Alberto ; Colonnese, Matthew ; Touboul, Jonathan.
info:eu-repo/semantics/altIdentifier/doi/10.1152/jn.00402.2019.  , 2020
Link: https://hal.science/hal-..
 
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11

Progressive alignment of inhibitory and excitatory delay ma..:

Romagnoni, Alberto ; Colonnese, Matthew ; Touboul, Jonathan.
info:eu-repo/semantics/altIdentifier/doi/10.1152/jn.00402.2019.  , 2020
Link: https://hal.science/hal-..
 
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12

Progressive alignment of inhibitory and excitatory delay ma..:

Romagnoni, Alberto ; Colonnese, Matthew T ; Touboul, Jonathan D.
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8086634/.  , 2020
Link: http://www.ncbi.nlm.nih...
 
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13

Comparative performances of machine learning methods for cl..:

Romagnoni, Alberto ; Jégou, Simon ; Van Steen, Kristel...
doi:10.17863/CAM.55156.  , 2020
Link: https://doi.org/10.17863..
 
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14

A deep learning model to predict RNA-Seq expression of tumo..:

Schmauch, Benoît ; Romagnoni, Alberto ; Pronier, Elodie...
info:eu-repo/semantics/altIdentifier/doi/10.1038/s41467-020-17678-4.  , 2020
Link: https://www.hal.inserm.f..
 
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15

A deep learning model to predict RNA-Seq expression of tumo..:

Schmauch, Benoît ; Romagnoni, Alberto ; Pronier, Elodie...
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7400514/.  , 2020
Link: http://www.ncbi.nlm.nih...
 
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