| JointDNN: An Efficient Training and Inference Engine for Intelligent Mobile Cloud Computing Services AE Eshratifar, MS Abrishami, M Pedram IEEE Transactions on Mobile Computing, 2019 | 431 | 2019 |
| BottleNet: A Deep Learning Architecture for Intelligent Mobile Cloud Computing Services AE Eshratifar, A Esmaili, M Pedram 2019 IEEE/ACM International Symposium on Low Power Electronics and Design …, 2019 | 255 | 2019 |
| Reliability-aware design to suppress aging H Amrouch, B Khaleghi, A Gerstlauer, J Henkel Proceedings of the 53rd Annual Design Automation Conference, 1-6, 2016 | 134 | 2016 |
| Energy and performance efficient computation offloading for deep neural networks in a mobile cloud computing environment AE Eshratifar, M Pedram Proceedings of the 2018 Great Lakes Symposium on VLSI, 111-116, 2018 | 127 | 2018 |
| Towards Collaborative Intelligence Friendly Architectures for Deep Learning AE Eshratifar, A Esmaili, M Pedram International Symposium on Quality Electronics Design, 2019, 2019 | 40 | 2019 |
| Video Person Re-ID: Fantastic Techniques and Where to Find Them P Pathak, AE Eshratifar, M Gormish Proceedings of the AAAI Conference on Artificial Intelligence 34 (10), 13893 …, 2020 | 38 | 2020 |
| Coarse2Fine: a two-stage training method for fine-grained visual classification AE Eshratifar, D Eigen, M Gormish, M Pedram Machine Vision and Applications 32 (2), 1-9, 2021 | 19 | 2021 |
| Gradient Agreement as an Optimization Objective for Meta-Learning AE Eshratifar, D Eigen, M Pedram NeurIPS Meta-learning Workshop, 2018 | 19 | 2018 |
| Runtime deep model multiplexing for reduced latency and energy consumption inference AE Eshratifar, M Pedram 2020 IEEE 38th International Conference on Computer Design (ICCD), 263-270, 2020 | 17* | 2020 |
| Salient Object-Aware Background Generation using Text-Guided Diffusion Models AE Eshratifar, JVB Soares, K Thadani, S Mishra, M Kuznetsov, YN Ku, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | 14 | 2024 |
| A hardware-friendly algorithm for scalable training and deployment of dimensionality reduction models on FPGA M Nazemi, AE Eshratifar, M Pedram International Symposium on Quality Electronics Design, 2018, 2018 | 13 | 2018 |
| A meta-learning approach for custom model training AE Eshratifar, MS Abrishami, D Eigen, M Pedram Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 9937-9938, 2019 | 8 | 2019 |
| Efficient Training of Deep Convolutional Neural Networks by Augmentation in Embedding Space MS Abrishami, AE Eshratifar, D Eigen, Y Wang, S Nazarian, M Pedram International Symposium on Quality Electronics Design, 2020, 2020 | 7 | 2020 |
| SCOT: Self-Supervised Contrastive Pretraining for Zero-Shot Compositional Retrieval B Jawade, JVB Soares, K Thadani, DD Mohan, AE Eshratifar, ... 2025 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV …, 2025 | 2 | 2025 |
| Variational Auto Encoder (VAE) for the Numerai Dataset E Eshratifar | 2 | 2022 |
| Systems and methods for image compositing via machine learning B JAWADE, AE ESHRATIFAR, K Thadani, P de Juan, JVB Soares, ... US Patent App. 19/072,081, 2025 | | 2025 |
| Systems and methods for automatically adding text content to generated images F PEREZ-SORROSAL, B JAWADE, E ESHRATIFAR, JVB Soares US Patent US20250166257A1, 2025 | | 2025 |
