E-LIB Suche - Ergebnisse für: Castorina, Leonardo V

1

TIMED-Design: flexible and accessible protein sequence desi..:

Castorina, Leonardo V ; Ünal, Suleyman Mert ; Subr, Kartic.
Protein Engineering, Design and Selection. 37 (2024) - p. , 2024

Link: https://doi.org/10.1093/..

2

PDBench: evaluating computational methods for protein-seque..:

Castorina, Leonardo V ; Petrenas, Rokas ; Subr, Kartic..
Bioinformatics. 39 (2023) 1 - p. , 2023

Link: https://doi.org/10.1093/..

3

Attentive Variational Information Bottleneck for TCR–peptid..:

Grazioli, Filippo ; Machart, Pierre ; Mösch, Anja...
Bioinformatics. 39 (2022) 1 - p. , 2022

Link: https://doi.org/10.1093/..

4

Deep attention super-resolution of brain magnetic resonance..:

Li, Bryan M. ; Castorina, Leonardo V. ; Valdés Hernández, Maria del C....
Frontiers in Computational Neuroscience. 16 (2022) - p. , 2022

Link: https://doi.org/10.3389/..

5

Deep attention super-resolution of brain magnetic resonance..:

Li, Bryan M ; Castorina, Leonardo V ; Valdés Hernández, Maria del C...
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9458316/. , 2022

Link: http://www.ncbi.nlm.nih...

6

Metrics for quality control of results from super-resolutio..:

Castorina, Leonardo V ; Li, Bryan M ; Storkey, Amos.
Castorina, Leonardo V.; Li, Bryan M.; Storkey, Amos; Valdés Hernández, Maria. (2021). Metrics for quality control of results from super-resolution machine-learning algorithms – Data extracted from publications in the period 2017- May 2021, 2017-2021 [dataset]. University of Edinburgh. Centre for Clinical Brain Sciences and School of Informatics. https://doi.org/10.7488/ds/3062.. , 2021

Link: https://hdl.handle.net/1..

7

PDBench: Evaluating Computational Methods for Protein Seque..:

Castorina, Leonardo V ; Petrenas, Rokas ; Subr, Kartic.
http://arxiv.org/abs/2109.07925. , 2021

Link: http://arxiv.org/abs/210..

8

Table_1_Deep attention super-resolution of brain magnetic r..:

Bryan M. Li ; Leonardo V. Castorina ; Maria del C. Valdés Hernández...
doi:10.3389/fncom.2022.887633.s002. , 2022

Link: https://doi.org/10.3389/..

9

Table_2_Deep attention super-resolution of brain magnetic r..:

Bryan M. Li ; Leonardo V. Castorina ; Maria del C. Valdés Hernández...
doi:10.3389/fncom.2022.887633.s003. , 2022

Link: https://doi.org/10.3389/..

10

Data_Sheet_1_Deep attention super-resolution of brain magne..:

Bryan M. Li ; Leonardo V. Castorina ; Maria del C. Valdés Hernández...
doi:10.3389/fncom.2022.887633.s001. , 2022

Link: https://doi.org/10.3389/..

11

Deep attention super-resolution of brain magnetic resonance..:

Bryan M. Li ; Leonardo V. Castorina ; Maria del C. Valdés Hernández...
https://www.frontiersin.org/articles/10.3389/fncom.2022.887633/full. , 2022

Link: https://doi.org/10.3389/..

12

Table_3_Deep attention super-resolution of brain magnetic r..:

Bryan M. Li ; Leonardo V. Castorina ; Maria del C. Valdés Hernández...
doi:10.3389/fncom.2022.887633.s004. , 2022

Link: https://doi.org/10.3389/..

13

TIMED-Design: Efficient Protein Sequence Design with Deep L..:

Leonardo V Castorina ; Kartic Subr ; Christopher W. Wood
https://github.com/wells-wood-research/timed-design/tree/v0.1-alpha. , 2022

Link: https://zenodo.org/recor..

14

Dark Matter Science in the Era of LSST:

Bechtol, Keith ; Drlica-Wagner, Alex ; Abazajian, Kevork N...
BULLETIN OF THE AMERICAN ASTRONOMICAL SOCIETY. , 2019

Link: https://hdl.handle.net/2..

15

Primordial Non-Gaussianity:

Meerburg, P. Daniel ; Green, Daniel ; Abidi, Muntazir...
http://arxiv.org/abs/1903.04409. , 2019

Link: http://arxiv.org/abs/190..