Neda Rohani
Neda Rohani
Applied Scientist at Microsoft
Verified email at
Cited by
Cited by
Gravity Spy: integrating advanced LIGO detector characterization, machine learning, and citizen science
M Zevin, S Coughlin, S Bahaadini, E Besler, N Rohani, S Allen, M Cabero, ...
Classical and Quantum Gravity 34 (6), 064003, 2017
Machine learning for Gravity Spy: Glitch classification and dataset
S Bahaadini, V Noroozi, N Rohani, S Coughlin, M Zevin, JR Smith, ...
Information Sciences 444, 172-186, 2018
Deep multi-view models for glitch classification
S Bahaadini, N Rohani, S Coughlin, M Zevin, V Kalogera, ...
2017 IEEE International Conference on Acoustics, Speech and Signal …, 2017
Classifying the unknown: Discovering novel gravitational-wave detector glitches using similarity learning
S Coughlin, S Bahaadini, N Rohani, M Zevin, O Patane, M Harandi, ...
Physical Review D 99 (8), 082002, 2019
Innovative data reduction and visualization strategy for hyperspectral imaging datasets using t-SNE approach
E Pouyet, N Rohani, AK Katsaggelos, O Cossairt, M Walton
Pure and Applied Chemistry 90 (3), 493-506, 2018
Guess and determine attack on trivium family
N Rohani, Z Noferesti, J Mohajeri, MR Aref
2010 IEEE/IFIP International Conference on Embedded and Ubiquitous Computing …, 2010
Direct: Deep discriminative embedding for clustering of ligo data
S Bahaadini, N Rohani, AK Katsaggelos, V Noroozi, S Coughlin, M Zevin
2018 25th IEEE International Conference on Image Processing (ICIP), 748-752, 2018
C. sterlund, JR Smith, L. Trouille, and V. Kalogera
M Zevin, S Coughlin, S Bahaadini, E Besler, N Rohani, S Allen, M Cabero, ...
Classical and Quantum Gravity 34, 064003, 2017
Nonlinear unmixing of hyperspectral datasets for the study of painted works of art
N Rohani, E Pouyet, M Walton, O Cossairt, AK Katsaggelos
Angewandte Chemie 130 (34), 11076-11080, 2018
Automatic pigment identification on roman egyptian paintings by using sparse modeling of hyperspectral images
N Rohani, J Salvant, S Bahaadini, O Cossairt, M Walton, A Katsaggelos
2016 24th European Signal Processing Conference (EUSIPCO), 2111-2115, 2016
Graph-based identification of boundary points for unmixing and anomaly detection
N Rohani, M Parente
2013 5th Workshop on Hyperspectral Image and Signal Processing: Evolution in …, 2013
Neural networks for modeling neural spiking in S1 cortex
A Lucas, T Tomlinson, N Rohani, R Chowdhury, SA Solla, ...
Frontiers in systems neuroscience 13, 13, 2019
Variational gaussian process for sensor fusion
N Rohani, P Ruiz, E Besler, R Molina, AK Katsaggelos
2015 23rd European Signal Processing Conference (EUSIPCO), 170-174, 2015
Distinguishing attack on bivium
Z Noferesti, N Rohani, J Mohajeri, MR Aref
2010 10th IEEE International Conference on Computer and Information …, 2010
Matrix sparsification and non-negative factorization for task partitioning in computational sensing and imaging
DG Stork, N Rohani, AK Katsaggelos
Computational Imaging II 10222, 102220P, 2017
Knowledge Tracing to Model Learning in Online Citizen Science Projects
K Crowston, C Østerlund, TK Lee, C Jackson, M Harandi, S Allen, ...
IEEE Transactions on Learning Technologies 13 (1), 123-134, 2019
Direct Estimation of Weights and Efficient Training of Deep Neural Networks without SGD
N Dehmamy, N Rohani, AK Katsaggelos
ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019
Variational Gaussian process for multisensor classification problems
N Rohani, P Ruiz, R Molina, AK Katsaggelos
Pattern Recognition Letters 116, 80-87, 2018
Separation of time scales and direct computation of weights in deep neural networks
N Dehmamy, N Rohani, A Katsaggelos
arXiv preprint arXiv:1703.04757, 2017
Convergence of Deep Neural Networks to a Hierarchical Covariance Matrix Decomposition
N Dehmamy, N Rohani, A Katsaggelos
Computing Research Repository 1703, 2017
The system can't perform the operation now. Try again later.
Articles 1–20