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Andrew Zalesky
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2020 – today
- 2023
- [j44]Martin Tik
, Michael Woletz
Acute TMS/fMRI response explains offline TMS network effects - An interleaved TMS-fMRI study. NeuroImage 267: 119833 (2023) - [j43]Yuanzhe Liu
Parameter estimation for connectome generative models: Accuracy, reliability, and a fast parameter fitting method. NeuroImage 270: 119962 (2023) - [j42]Léonie Borne
Functional re-organization of hippocampal-cortical gradients during naturalistic memory processes. NeuroImage 271: 119996 (2023) - [j41]Gabriel Girard, Jonathan Rafael-Patino, Raphaël Truffet, Dogu Baran Aydogan, Nagesh Adluru, Veena A. Nair, Vivek Prabhakaran, Barbara B. Bendlin
Tractography passes the test: Results from the diffusion-simulated connectivity (disco) challenge. NeuroImage 277: 120231 (2023) - [j40]Tabinda Sarwar
Evaluation of tractogram filtering methods using human-like connectome phantoms. NeuroImage 281: 120376 (2023) - [j39]Sina Mansour L
Connectomes for 40,000 UK Biobank participants: A multi-modal, multi-scale brain network resource. NeuroImage 283: 120407 (2023) - 2022
- [j38]Amir H. Omidvarnia
On the Spatial Distribution of Temporal Complexity in Resting State and Task Functional MRI. Entropy 24(8): 1148 (2022) - [j37]Sina Mansour L
Connectome spatial smoothing (CSS): Concepts, methods, and evaluation. NeuroImage 250: 118930 (2022) - [j36]Caio Seguin
Network communication models narrow the gap between the modular organization of structural and functional brain networks. NeuroImage 257: 119323 (2022) - [j35]Johanna M. M. Bayer
Accommodating site variation in neuroimaging data using normative and hierarchical Bayesian models. NeuroImage 264: 119699 (2022) - 2021
- [j34]Tabinda Sarwar
Structure-function coupling in the human connectome: A machine learning approach. NeuroImage 226: 117609 (2021) - [j33]Sina Mansour L
High-resolution connectomic fingerprints: Mapping neural identity and behavior. NeuroImage 229: 117695 (2021) - [j32]Amir H. Omidvarnia
Temporal complexity of fMRI is reproducible and correlates with higher order cognition. NeuroImage 230: 117760 (2021) - [j31]Emin Serin
NBS-Predict: A prediction-based extension of the network-based statistic. NeuroImage 244: 118625 (2021) - [j30]Ye Tian
Machine learning prediction of cognition from functional connectivity: Are feature weights reliable? NeuroImage 245: 118648 (2021) - 2020
- [j29]Tabinda Sarwar
Towards deep learning for connectome mapping: A block decomposition framework. NeuroImage 212: 116654 (2020)
2010 – 2019
- 2018
- [j28]Mangor Pedersen, Amir H. Omidvarnia
On the relationship between instantaneous phase synchrony and correlation-based sliding windows for time-resolved fMRI connectivity analysis. NeuroImage 181: 85-94 (2018) - [j27]Ye Tian
Characterizing the functional connectivity diversity of the insula cortex: Subregions, diversity curves and behavior. NeuroImage 183: 716-733 (2018) - 2017
- [j26]Martijn P. van den Heuvel
Proportional thresholding in resting-state fMRI functional connectivity networks and consequences for patient-control connectome studies: Issues and recommendations. NeuroImage 152: 437-449 (2017) - [j25]Andrew Zalesky
Functional architecture of the human brain. NeuroImage 160: 1 (2017) - 2016
- [j24]Dimitri Van De Ville
Introduction to the Issue on Advanced Signal Processing for Brain Networks. IEEE J. Sel. Top. Signal Process. 10(7): 1131-1133 (2016) - [j23]Deanne K. Thompson
Structural connectivity relates to perinatal factors and functional impairment at 7 years in children born very preterm. NeuroImage 134: 328-337 (2016) - [j22]Andrew Zalesky
Connectome sensitivity or specificity: which is more important? NeuroImage 142: 407-420 (2016) - 2015
- [j21]Andrew Zalesky
Towards a statistical test for functional connectivity dynamics. NeuroImage 114: 466-470 (2015) - 2013
- [j20]Alex Fornito, Andrew Zalesky
Graph analysis of the human connectome: Promise, progress, and pitfalls. NeuroImage 80: 426-444 (2013) - 2012
- [j19]Andrew Zalesky
Connectivity differences in brain networks. NeuroImage 60(2): 1055-1062 (2012) - [j18]Andrew Zalesky
On the use of correlation as a measure of network connectivity. NeuroImage 60(4): 2096-2106 (2012) - [j17]Alex Fornito, Andrew Zalesky
Schizophrenia, neuroimaging and connectomics. NeuroImage 62(4): 2296-2314 (2012) - 2010
- [j16]Andrew Zalesky
Whole-brain anatomical networks: Does the choice of nodes matter? NeuroImage 50(3): 970-983 (2010) - [j15]Andrew Zalesky
Network-based statistic: Identifying differences in brain networks. NeuroImage 53(4): 1197-1207 (2010)
2000 – 2009
- 2009
- [j14]Eric W. M. Wong
A state-dependent approximation for the generalized Engset model. IEEE Commun. Lett. 13(12): 962-964 (2009) - [j13]Andrew Zalesky
A DTI-Derived Measure of Cortico-Cortical Connectivity. IEEE Trans. Medical Imaging 28(7): 1023-1036 (2009) - [j12]Andrew Zalesky:
To burst or circuit switch? IEEE/ACM Trans. Netw. 17(1): 305-318 (2009) - [c8]Andrew Zalesky
Engset Formula for Bufferless OBS/OPS: When Is and When Isn't Lengthening the Off-Time Redundant? GLOBECOM 2009: 1-6 - 2008
- [j11]Andrew Zalesky
DT-MRI Fiber Tracking: A Shortest Paths Approach. IEEE Trans. Medical Imaging 27(10): 1458-1471 (2008) - 2007
- [j10]Eric W. M. Wong
A new method for approximating blocking probability in overflow loss networks. Comput. Networks 51(11): 2958-2975 (2007) - [j9]Eric W. M. Wong
On Generalizations of the Engset Model. IEEE Commun. Lett. 11(4): 360-362 (2007) - [j8]Garvesh Raskutti, Andrew Zalesky
Enhanced Blocking Probability Evaluation Method for Circuit-Switched Trunk Reservation Networks. IEEE Commun. Lett. 11(6): 543-545 (2007) - [j7]Andrew Zalesky
Stabilizing deflection routing in optical burst switched networks. IEEE J. Sel. Areas Commun. 25(S-6): 3-19 (2007) - [j6]Andrew Zalesky
OBS contention resolution performance. Perform. Evaluation 64(4): 357-373 (2007) - [c7]Garvesh Raskutti, Andrew Zalesky
Blocking Probability Estimation for Trunk Reservation Networks. ICC 2007: 223-228 - [c6]Jayant Baliga, Andrew Zalesky
Effect of Traffic Shifts on the Economics of Telecommunication Competition. ICC 2007: 229-234 - 2006
- [j5]Zvi Rosberg, Andrew Zalesky, Moshe Zukerman:
Packet delay in optical circuit-switched networks. IEEE/ACM Trans. Netw. 14(2): 341-354 (2006) - [j4]Zvi Rosberg, Andrew Zalesky, Hai Le Vu, Moshe Zukerman:
Analysis of OBS networks with limited wavelength conversion. IEEE/ACM Trans. Netw. 14(5): 1118-1127 (2006) - [c5]Andrew Zalesky
Optimizing an OBS scheduler buffer. VALUETOOLS 2006: 22 - 2005
- [j3]Craig W. Cameron, Andrew Zalesky
Prioritized Deflection Routing in Optical Burst Switching Networks. IEICE Trans. Commun. 88-B(5): 1861-1867 (2005) - [c4]Eric W. M. Wong, Michael Y. M. Chiu, Moshe Zukerman, Zvi Rosberg, Sammy Chan, Andrew Zalesky:
A novel method for modeling and analysis of distributed video on demand systems. ICC 2005: 88-92 - [c3]Hai Le Vu, Andrew Zalesky, Moshe Zukerman, Zvi Rosberg, Jun Guo, Tai-Won Um:
Delay analysis of optical burst switching networks. ICC 2005: 1656-1662 - 2004
- [j2]Andrew Zalesky
Reducing spare capacity through traffic splitting. IEEE Commun. Lett. 8(9): 594-596 (2004) - [c2]Andrew Zalesky, Hai Le Vu, Moshe Zukerman, Zvi Rosberg, Eric W. M. Wong:
Evaluation of limited wavelength conversion and deflection routing as methods to reduce blocking probability in optical burst switched networks. ICC 2004: 1543-1547 - [c1]Andrew Zalesky
Modeling and Performance Evaluation of Optical Burst Switched Networks with Deflection Routing and Wavelength Reservation. INFOCOM 2004: 1864-1871 - 2003
- [j1]Andrew Zalesky
A framework for solving logical topology design problems within constrained computation time. IEEE Commun. Lett. 7(10): 499-501 (2003)
Coauthor Index
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last updated on 2024-10-07 21:23 CEST by the dblp team
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