Vahid Partovi Nia
Vahid Partovi Nia
Huawei Noah's Ark Lab and Ecole Polytechnique de Montreal
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Cited by
Cited by
Rapid classification of phenotypic mutants of Arabidopsis via metabolite fingerprinting
G Messerli, V Partovi Nia, M Trevisan, A Kolbe, N Schauer, ...
Plant Physiology 143 (4), 1484-1492, 2007
Multiomics modeling of the immunome, transcriptome, microbiome, proteome and metabolome adaptations during human pregnancy
MS Ghaemi, DB DiGiulio, K Contrepois, B Callahan, TTM Ngo, ...
Bioinformatics 35 (1), 95-103, 2019
Regularized Binary Network Training
S Darabi, M Belbahri, M Courbariaux, V Partovi Nia
NeurIPS 2019 EMC2 Workshop, 2019
Testing multiple variance components in linear mixed-effects models
R Drikvandi, G Verbeke, A Khodadadi, V Partovi Nia
Biostatistics 14 (1), 144-159, 2013
A visual segmentation method for temporal smart card data
MS Ghaemi, B Agard, M Trépanier, V Partovi Nia
Transportmetrica A: Transport Science 13 (5), 381-404, 2017
Assessing public transport travel behaviour from smart card data with advanced data mining techniques
B Agard, V Partovi Nia, M Trépanier
World Conference on Transport Research 13, 15-18, 2013
High-Dimensional Bayesian Clustering with Variable Selection: The R Package bclust
V Partovi Nia, AC Davison
Journal of Statistical Software 47 (ARTICLE), 1-22, 2012
On characterizing full dimensional weak facets in DEA with variable returns to scale technology
M Davtalab-Olyaie, I Roshdi, V Partovi Nia, M Asgharian
Optimization 64 (11), 2455-2476, 2015
Challenges in spatial-temporal data analysis targeting public transport
MS Ghaemi, B Agard, V Partovi Nia, M Trépanier
IFAC-PapersOnLine 48 (3), 442-447, 2015
A consistent confidence interval for fuzzy capability index
A Parchami, M Mashinchi, V Partovi Nia
Applied and Computational Mathematics 7 (ARTICLE), 119-125, 2008
How does batch normalization help binary training?
E Sari, M Belbahri, VP Nia
arXiv preprint arXiv:1909.09139, 2019
Impact of occupational exposure to chemicals in life cycle assessment: a novel characterization model based on measured concentrations and labor hours
G Kijko, M Margni, V Partovi Nia, G Doudrich, O Jolliet
Environmental science & technology 49 (14), 8741-8750, 2015
Causal inference and mechanism clustering of a mixture of additive noise models
S Hu, Z Chen, V Partovi Nia, C Laiwan, Y Geng
Advances in Neural Information Processing Systems, 5206-5216, 2018
Flight deck crew reserve: From data to forecasting
AH Homaie-Shandizi, V Partovi Nia, M Gamache, B Agard
Engineering Applications of Artificial Intelligence 50, 106-114, 2016
Differentiable mask for pruning convolutional and recurrent networks
RK Ramakrishnan, E Sari, VP Nia
2020 17th Conference on Computer and Robot Vision (CRV), 222-229, 2020
Activation adaptation in neural networks
F Farhadi, VP Nia, A Lodi
arXiv preprint arXiv:1901.09849, 2019
A simple model‐based approach to variable selection in classification and clustering
V Partovi Nia, AC Davison
Canadian Journal of Statistics 43 (2), 157-175, 2015
Fast high-dimensional Bayesian classification and clustering
V Partovi Nia
EPFL, 2009
Gauss-hermite quadrature: Numerical or statistical method?
V Partovi Nia
Proc. Iranian Stat. Conf, 209-215, 2006
Binary quantizer
VP Nia, M Belbahri
Journal of Computational Vision and Imaging Systems 4 (1), 3-3, 2018
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