| Inverse-designed low-loss and wideband polarization-insensitive silicon waveguide crossing Z Yu, A Feng, X Xi, X Sun Optics Letters 44 (1), 77-80, 2019 | 50 | 2019 |
| Kergnns: Interpretable graph neural networks with graph kernels A Feng, C You, S Wang, L Tassiulas Proceedings of the AAAI conference on artificial intelligence 36 (6), 6614-6622, 2022 | 47 | 2022 |
| Adaptive graph spatial-temporal transformer network for traffic forecasting A Feng, L Tassiulas Proceedings of the 31st ACM international conference on information …, 2022 | 23 | 2022 |
| Megan: memory enhanced graph attention network for space-time video super-resolution C You, L Han, A Feng, R Zhao, H Tang, W Fan Proceedings of the IEEE/CVF winter conference on applications of computer …, 2022 | 15 | 2022 |
| Designing data center networks using bottleneck structures J Ros-Giralt, N Amsel, S Yellamraju, J Ezick, R Lethin, Y Jiang, A Feng, ... Proceedings of the 2021 ACM SIGCOMM 2021 Conference, 319-348, 2021 | 8 | 2021 |
| Diffuser: efficient transformers with multi-hop attention diffusion for long sequences A Feng, I Li, Y Jiang, R Ying Proceedings of the AAAI Conference on Artificial Intelligence 37 (11), 12772 …, 2023 | 7 | 2023 |
| DINC: Toward distributed in-network computing C Zheng, H Tang, M Zang, X Hong, A Feng, L Tassiulas, N Zilberman Proceedings of the ACM on Networking 1 (CoNEXT3), 1-25, 2023 | 5 | 2023 |
| LiGCN: label-interpretable graph convolutional networks for multi-label text classification I Li, A Feng, H Wu, T Li, T Suzumura, R Dong arXiv preprint arXiv:2103.14620, 2021 | 4 | 2021 |
| A quantitative theory of bottleneck structures for data networks J Ros-Giralt, N Amsel, S Yellamraju, J Ezick, R Lethin, Y Jiang, A Feng, ... arXiv preprint arXiv:2210.03534, 2022 | 3 | 2022 |
| Energy-efficient and robust cumulative training with net2net transformation A Feng, P Panda 2020 International Joint Conference on Neural Networks (IJCNN), 1-7, 2020 | 3 | 2020 |
| Giant enhancement of nonlinear optical processes with split-ring resonators for thz applications A Feng, Z Yu, X Sun IEEE Photonics Technology Letters 31 (21), 1681-1684, 2019 | 3 | 2019 |
| Integrating view conditions for image synthesis J Bai, Z Dong, A Feng, X Zhang, T Ye, K Zhou, MZ Shou arXiv preprint arXiv:2310.16002, 2023 | 2 | 2023 |
| HiPool: Modeling long documents using graph neural networks I Li, A Feng, D Radev, R Ying arXiv preprint arXiv:2305.03319, 2023 | 2 | 2023 |
| Efficient High-Resolution Time Series Classification via Attention Kronecker Decomposition A Feng, J Chen, J Garza, B Berry, F Salazar, Y Gao, R Ying, L Tassiulas arXiv preprint arXiv:2403.04882, 2024 | 1 | 2024 |
| Solving General Noisy Inverse Problem via Posterior Sampling: A Policy Gradient Viewpoint H Tang, T Xie, A Feng, H Wang, C Zhang, Y Bai International Conference on Artificial Intelligence and Statistics, 2116-2124, 2024 | | 2024 |
| From Similarity to Superiority: Channel Clustering for Time Series Forecasting J Chen, JE Lenssen, A Feng, W Hu, M Fey, L Tassiulas, J Leskovec, ... arXiv preprint arXiv:2404.01340, 2024 | | 2024 |
| An Item is Worth a Prompt: Versatile Image Editing with Disentangled Control A Feng, W Qiu, J Bai, K Zhou, Z Dong, X Zhang, R Ying, L Tassiulas arXiv preprint arXiv:2403.04880, 2024 | | 2024 |
| Leveraging Large Language Models for Concept Graph Recovery and Question Answering in NLP Education R Yang, B Yang, S Ouyang, T She, A Feng, Y Jiang, F Lecue, J Lu, I Li arXiv preprint arXiv:2402.14293, 2024 | | 2024 |
| Solving Noisy Inverse Problems via Posterior Sampling: A Policy Gradient View-Point H Tang, T Xie, A Feng, H Wang, C Zhang, Y Bai The Symbiosis of Deep Learning and Differential Equations III, 2023 | | 2023 |
