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Iman Deznabi
Iman Deznabi
PhD candidate, Manning College of Information & Computer Sciences, University of Massachusetts
Verifisert e-postadresse på cs.umass.edu - Startside
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An inference attack on genomic data using kinship, complex correlations, and phenotype information
I Deznabi, M Mobayen, N Jafari, O Tastan, E Ayday
IEEE/ACM transactions on computational biology and bioinformatics 15 (4 …, 2017
572017
DeepKinZero: zero-shot learning for predicting kinase–phosphosite associations involving understudied kinases
I Deznabi, B Arabaci, M Koyutürk, O Tastan
Bioinformatics 36 (12), 3652-3661, 2020
422020
Predicting in-hospital mortality by combining clinical notes with time-series data
I Deznabi, M Iyyer, M Fiterau
Findings of the association for computational linguistics: ACL-IJCNLP 2021 …, 2021
392021
Population‐level inference for home‐range areas
CH Fleming, I Deznabi, S Alavi, MC Crofoot, BT Hirsch, EP Medici, ...
Methods in Ecology and Evolution 13 (5), 1027-1041, 2022
262022
Impact of the COVID-19 Pandemic on the Academic Community Results from a survey conducted at University of Massachusetts Amherst
I Deznabi, T Motahar, A Sarvghad, M Fiterau, N Mahyar
Digital Government: Research and Practice 2 (2), 1-12, 2021
202021
Personalized student stress prediction with deep multitask network
A Shaw, N Simsiri, I Deznaby, M Fiterau, T Rahaman
arXiv preprint arXiv:1906.11356, 2019
172019
Multi-resolution networks for flexible irregular time series modeling (multi-fit)
BP Singh, I Deznabi, B Narasimhan, B Kucharski, R Uppaal, A Josyula, ...
arXiv preprint arXiv:1905.00125, 2019
132019
Multiwave: Multiresolution deep architectures through wavelet decomposition for multivariate time series prediction
I Deznabi, M Fiterau
Conference on Health, Inference, and Learning, 509-525, 2023
52023
Dynamic clustering via branched deep learning enhances personalization of stress prediction from mobile sensor data
Y Luo, I Deznabi, A Shaw, N Simsiri, T Rahman, M Fiterau
Scientific Reports 14 (1), 6631, 2024
32024
MEMNAR: Finding mutually exclusive mutation sets through negative association rule mining
I Deznabi, AA Celik, O Tastan
International Workshop on Machine Learning in Systems Biology, 2017
12017
Zero-shot Microclimate Prediction with Deep Learning
I Deznabi, P Kumar, M Fiterau
arXiv preprint arXiv:2401.02665, 2024
2024
Towards Resolution-Aware Retrieval Augmented Zero-Shot Forecasting
I Deznabi, P Kumar, M Fiterau
NeurIPS Workshop on Time Series in the Age of Large Models, 0
DeepKinZero: Zero-Shot Learning for Predicting Kinase-Phosphosite Associations
I Deznabi, B Arabaci, M Koyuturk, O Tastan
Multi-resolution Attention with Signal Splitting for Multivariate Time Series Classification
R Uppaal, B Kucharski, BP Singh, I Deznabi, M Fiterau
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Artikler 1–14