| Fusing heterogeneous data: A case for remote sensing and social media H Wang, E Skau, H Krim, G Cervone IEEE Transactions on Geoscience and Remote Sensing 56 (12), 6956-6968, 2018 | 59 | 2018 |
| Finding the number of latent topics with semantic non-negative matrix factorization R Vangara, M Bhattarai, E Skau, G Chennupati, H Djidjev, T Tierney, ... IEEE access 9, 117217-117231, 2021 | 37 | 2021 |
| Distributed non-negative matrix factorization with determination of the number of latent features G Chennupati, R Vangara, E Skau, H Djidjev, B Alexandrov The Journal of Supercomputing 76, 7458-7488, 2020 | 25 | 2020 |
| Semantic nonnegative matrix factorization with automatic model determination for topic modeling R Vangara, E Skau, G Chennupati, H Djidjev, T Tierney, JP Smith, ... 2020 19th IEEE International Conference on Machine Learning and Applications …, 2020 | 21 | 2020 |
| Distributed non-negative tensor train decomposition M Bhattarai, G Chennupati, E Skau, R Vangara, H Djidjev, BS Alexandrov 2020 IEEE High Performance Extreme Computing Conference (HPEC), 1-10, 2020 | 20 | 2020 |
| Image classification: A hierarchical dictionary learning approach S Mahdizadehaghdam, L Dai, H Krim, E Skau, H Wang 2017 IEEE International Conference on Acoustics, Speech and Signal …, 2017 | 16 | 2017 |
| General-purpose unsupervised cyber anomaly detection via non-negative tensor factorization ME Eren, JS Moore, E Skau, E Moore, M Bhattarai, G Chennupati, ... Digital Threats: Research and Practice 4 (1), 1-28, 2023 | 12 | 2023 |
| Factorizations of binary matrices-rank relations and the uniqueness of Boolean decompositions D DeSantis, E Skau, BS Alexandrov CoRR, 2020 | 12* | 2020 |
| pydnmfk: Python distributed non negative matrix factorization M Bhattarai, B Nebgen, E Skau, M Eren, G Chennupati, R Vangara, ... GitHub. DOI: https://doi. org/10.5281/zenodo 4722448, 2021 | 10 | 2021 |
| Distributed non-negative rescal with automatic model selection for exascale data M Bhattarai, I Boureima, E Skau, B Nebgen, H Djidjev, S Rajopadhye, ... Journal of Parallel and Distributed Computing 179, 104709, 2023 | 8 | 2023 |
| Challenging the curse of dimensionality in multidimensional numerical integration by using a low-rank tensor-train format B Alexandrov, G Manzini, EW Skau, PMD Truong, RG Vuchov Mathematics 11 (3), 534, 2023 | 8 | 2023 |
| Determination of latent dimensionality in international trade flow DP Truong, E Skau, VI Valtchinov, BS Alexandrov Machine Learning: Science and Technology 1 (4), 045017, 2020 | 8 | 2020 |
| Distributed out-of-memory NMF on CPU/GPU architectures I Boureima, M Bhattarai, M Eren, E Skau, P Romero, S Eidenbenz, ... The Journal of Supercomputing 80 (3), 3970-3999, 2024 | 6 | 2024 |
| Tensor Extraction of Latent Features (TELF) M Eren, B Alexandrov, M Bhattarai, K Rasmussen, E Skau, D Truong, ... Los Alamos National Laboratory (LANL), Los Alamos, NM (United States), 2024 | 5 | 2024 |
| Nonnegative tensor-train low-rank approximations of the Smoluchowski coagulation equation G Manzini, E Skau, DP Truong, R Vangara International Conference on Large-Scale Scientific Computing, 342-350, 2021 | 5 | 2021 |
| Nonnegative canonical polyadic decomposition with rank deficient factors B Alexandrov, D DeSantis, G Manzini, E Skau arXiv preprint arXiv:1909.07570 3, 2019 | 5 | 2019 |
| A fast parallel algorithm for convolutional sparse coding E Skau, B Wohlberg 2018 IEEE 13th Image, Video, and Multidimensional Signal Processing Workshop …, 2018 | 5 | 2018 |
| Nonnegative canonical tensor decomposition with linear constraints: nnCANDELINC B Alexandrov, DF DeSantis, G Manzini, EW Skau Numerical Linear Algebra with Applications 29 (6), e2443, 2022 | 4 | 2022 |
| Distributed Out-of-core NMF of Dense and Sparse Data on CPU/GPU Architectures with Automatic Model Selection for Exascale Data I Boureima, M Bhattarai, M Eren, E Skau, P Romero, S Eidenbenz, ... | 4 | 2022 |
| Automatic model determination for quaternion nmf G Sanchez, E Skau, B Alexandrov IEEE access 9, 152243-152249, 2021 | 4 | 2021 |
