| Quantum Hall effect based on Weyl orbits in Cd3As2 C Zhang, Y Zhang, X Yuan, S Lu, J Zhang, A Narayan, Y Liu, H Zhang, ... Nature 565 (7739), 331-336, 2019 | 230 | 2019 |
| Inducing Strong Superconductivity in WTe2 by a Proximity Effect C Huang, A Narayan, E Zhang, Y Liu, X Yan, J Wang, C Zhang, W Wang, ... ACS nano 12 (7), 7185-7196, 2018 | 64 | 2018 |
| Proximity-induced surface superconductivity in Dirac semimetal Cd3As2 C Huang, BT Zhou, H Zhang, B Yang, R Liu, H Wang, Y Wan, K Huang, ... Nature communications 10 (1), 2217, 2019 | 63 | 2019 |
| Mine your own view: Self-supervised learning through across-sample prediction M Azabou, MG Azar, R Liu, CH Lin, EC Johnson, K Bhaskaran-Nair, ... arXiv preprint arXiv:2102.10106, 2021 | 43 | 2021 |
| Drop, swap, and generate: A self-supervised approach for generating neural activity R Liu, M Azabou, M Dabagia, CH Lin, M Gheshlaghi Azar, KB Hengen, ... Advances in Neural Information Processing Systems 34, 10587-10599, 2021 | 30* | 2021 |
| Understand and improve contrastive learning methods for visual representation: A review R Liu arXiv preprint arXiv:2106.03259, 2021 | 11 | 2021 |
| Seeing the forest and the tree: Building representations of both individual and collective dynamics with transformers R Liu, M Azabou, M Dabagia, J Xiao, E Dyer Advances in neural information processing systems 35, 2377-2391, 2022 | 10 | 2022 |
| Half-Hop: A graph upsampling approach for slowing down message passing M Azabou, V Ganesh, S Thakoor, CH Lin, L Sathidevi, R Liu, M Valko, ... International Conference on Machine Learning, 1341-1360, 2023 | 6 | 2023 |
| Multi-scale modeling of neural structure in X-ray imagery A Balwani, J Miano, R Liu, L Kitchell, JA Prasad, EC Johnson, ... 2021 IEEE International Conference on Image Processing (ICIP), 141-145, 2021 | 5 | 2021 |
| Mtneuro: A benchmark for evaluating representations of brain structure across multiple levels of abstraction J Quesada, L Sathidevi, R Liu, N Ahad, J Jackson, M Azabou, J Xiao, ... Advances in neural information processing systems 35, 5299-5314, 2022 | 3 | 2022 |
| A generative modeling approach for interpreting population-level variability in brain structure R Liu, C Subakan, AH Balwani, J Whitesell, J Harris, S Koyejo, EL Dyer Medical Image Computing and Computer Assisted Intervention–MICCAI 2020: 23rd …, 2020 | 3 | 2020 |
| Frequency-aware masked autoencoders for multimodal pretraining on biosignals R Liu, EL Zippi, H Pouransari, C Sandino, J Nie, H Goh, E Azemi, A Moin arXiv preprint arXiv:2309.05927, 2023 | 2 | 2023 |
| Building representations of different brain areas through hierarchical point cloud networks JM Jackson, R Liu, EL Dyer Medical imaging with deep learning, 2022 | 2 | 2022 |
| Using self-supervision and augmentations to build insights into neural coding M Azabou, M Dabagia, R Liu, CH Lin, KB Hengen, WUS Louis, EL Dyer Proceedings of Workshop on Self-Supervised Learning-Theory and Practice on …, 2021 | 2 | 2021 |
| Balanced Data, Imbalanced Spectra: Unveiling Class Disparities with Spectral Imbalance C Kaushik*, R Liu*, CH Lin, A Khera, MY Jin, W Ma, V Muthukumar, ... arXiv preprint arXiv:2402.11742, 2024 | | 2024 |
| LatentDR: Improving Model Generalization Through Sample-Aware Latent Degradation and Restoration R Liu, S Khose, J Xiao, L Sathidevi, K Ramnath, Z Kira, EL Dyer Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2024 | | 2024 |
| GAFormer: Enhancing Timeseries Transformers Through Group-Aware Embeddings J Xiao, R Liu, EL Dyer The Twelfth International Conference on Learning Representations, 2023 | | 2023 |
Eva L. DyerGeorgia Institute of TechnologyVerified email at gatech.edu
