| Variational Graph Recurrent Neural Networks E Hajiramezanali, A Hasanzadeh, N Duffield, KR Narayanan, M Zhou, ... Advances in Neural Information Processing Systems (NeurIPS2019), 2019 | 226 | 2019 |
| Semi-Implicit Graph Variational Auto-Encoders A Hasanzadeh, E Hajiramezanali, N Duffield, KR Narayanan, M Zhou, ... Advances in Neural Information Processing Systems (NeurIPS2019), 2019 | 153 | 2019 |
| Bayesian Graph Neural Networks with Adaptive Connection Sampling A Hasanzadeh, E Hajiramezanali, S Boluki, M Zhou, N Duffield, ... International Conference on Machine Learning (ICML2020), 2020 | 144 | 2020 |
| Network-principled deep generative models for designing drug combinations as graph sets M Karimi, A Hasanzadeh, Y Shen Bioinformatics 36 (Supplement_1), i445-i454, 2020 | 32 | 2020 |
| Fault detection and isolation in industrial networks using graph convolutional neural networks H Khorasgani, A Hasanzadeh, A Farahat, C Gupta 2019 IEEE International Conference on Prognostics and Health Management …, 2019 | 31 | 2019 |
| Piecewise Stationary Modeling of Random Processes Over Graphs With an Application to Traffic Prediction A Hasanzadeh, X Liu, N Duffield, KR Narayanan 2019 IEEE International Conference on Big Data (Big Data), 3779-3788, 2019 | 29* | 2019 |
| Variational graph recurrent neural networks A Hasanzadeh, E Hajiramezanali, K Narayanan, N Duffield, M Zhou, ... Advances in neural information processing systems 32, 2019 | 17 | 2019 |
| BayReL: Bayesian Relational Learning for Multi-omics Data Integration E Hajiramezanali, A Hasanzadeh, N Duffield, K Narayanan, X Qian Advances in Neural Information Processing Systems (NeurIPS2020), 2020 | 15 | 2020 |
| MoReL: Multi-omics Relational Learning A Hasanzadeh, E Hajiramezanali, N Duffield, X Qian International Conference on Learning Representations (ICLR2022), 2022 | 7 | 2022 |
| Semi-Implicit Stochastic Recurrent Neural Networks E Hajiramezanali, A Hasanzadeh, N Duffield, K Narayanan, M Zhou, ... ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020 | 6 | 2020 |
| Bayesian graph contrastive learning A Hasanzadeh, M Armandpour, E Hajiramezanali, M Zhou, N Duffield, ... arXiv preprint arXiv:2112.07823, 2021 | 5 | 2021 |
| Rate selection and power adaptation using maximal ratio combining for the random access Gaussian channel A Hasanzadeh, JF Chamberland, K Narayanan arXiv preprint arXiv:1801.03557, 2018 | 3 | 2018 |
| Adaptive conditional quantile neural processes P Mohseni, N Duffield, B Mallick, A Hasanzadeh Uncertainty in Artificial Intelligence, 1445-1455, 2023 | | 2023 |
| System and method for maintenance recommendation in industrial networks H Khorasgani, C Gupta, AK Farahat, A Hasanzadehmoghimi US Patent App. 16/433,858, 2020 | | 2020 |
| Spatially-Coupled Neural Network Architectures A Hasanzadeh, NT Janakiraman, VK Amalladinne, KR Narayanan arXiv preprint arXiv:1907.02051, 2019 | | 2019 |
| Machine Learning for Genomics Explorations (MLGenX) E Hajiramezanali, C Bunne, A Hasanzadeh, T Biancalani, E Nguyen, ... ICLR 2024 Workshops, 0 | | |
| Adaptive Conditional Quantile Neural Processes (Supplementary material) P Mohseni, N Duffield, B Mallick, A Hasanzadeh | | |
| BayReL: Bayesian Relational Learning for Multi-omics Data Integration: Supplementary Materials E Hajiramezanali, A Hasanzadeh, N Duffield, K Narayanan, X Qian | | |
| Semi-Implicit Graph Variational Auto-Encoders: Supplementary Material A Hasanzadeh, E Hajiramezanali, N Duffield, K Narayanan, M Zhou, ... | | |
| Variational Graph Recurrent Neural Networks: Supplementary Material E Hajiramezanali, A Hasanzadeh, N Duffield, K Narayanan, M Zhou, ... | | |
Nick DuffieldDirector, Texas A&M Institute of Data Science; Royce E. Wisenbaker Professorship I in ECECorreu electrònic verificat a ece.tamu.edu