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 | 158 | 2019 |
Regularized Binary Network Training S Darabi, M Belbahri, M Courbariaux, V Partovi Nia NeurIPS 2019 EMC2 Workshop, 2019 | 151* | 2019 |
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 | 100 | 2007 |
Testing multiple variance components in linear mixed-effects models R Drikvandi, G Verbeke, A Khodadadi, V Partovi Nia Biostatistics 14 (1), 144-159, 2013 | 83 | 2013 |
Krona: Parameter efficient tuning with kronecker adapter A Edalati, M Tahaei, I Kobyzev, VP Nia, JJ Clark, M Rezagholizadeh arXiv preprint arXiv:2212.10650, 2022 | 60 | 2022 |
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 | 60 | 2017 |
How does batch normalization help binary training? E Sari, M Belbahri, VP Nia arXiv preprint arXiv:1909.09139, 2019 | 44 | 2019 |
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 | 35 | 2012 |
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 | 34 | 2013 |
Kronecker decomposition for gpt compression A Edalati, M Tahaei, A Rashid, VP Nia, JJ Clark, M Rezagholizadeh arXiv preprint arXiv:2110.08152, 2021 | 25 | 2021 |
Method and system for training binary quantized weight and activation function for deep neural networks LI Xinlin, S Darabi, M Belbahri, VP NIA US Patent App. 16/582,131, 2020 | 25 | 2020 |
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 | 24 | 2018 |
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 | 23 | 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 | 22 | 2015 |
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 | 20 | 2015 |
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 | 19 | 2020 |
A consistent confidence interval for fuzzy capability index A Parchami, M Mashinchi, V Partovi Nia Applied and Computational Mathematics 7 (1), 119-125, 2008 | 19 | 2008 |
Convolutional Neural Network Compression through Generalized Kronecker Product Decomposition MGA Hameed, MS Tahaei, A Mosleh, V Partovi Nia arXiv preprint arXiv:2109.14710, 2021 | 18 | 2021 |
KroneckerBERT: Learning Kronecker Decomposition for Pre-trained Language Models via Knowledge Distillation MS Tahaei, E Charlaix, V Partovi Nia, A Ghodsi, M Rezagholizadeh arXiv preprint arXiv:2109.06243, 2021 | 18 | 2021 |
Stochastic ranking and dominance in DEA M Davtalab-Olyaie, M Asgharian, V Partovi Nia International Journal of Production Economics 214, 125-138, 2019 | 18 | 2019 |