Predicting COVID-19 in China using hybrid AI model N Zheng, S Du, J Wang, H Zhang, W Cui, Z Kang, T Yang, B Lou, Y Chi, ... IEEE transactions on cybernetics 50 (7), 2891-2904, 2020 | 307 | 2020 |
Design space exploration of neural network activation function circuits T Yang, Y Wei, Z Tu, H Zeng, MA Kinsy, N Zheng, P Ren IEEE Transactions on Computer-Aided Design of Integrated Circuits and …, 2018 | 58 | 2018 |
Learning Disentangled Representation by Exploiting Pretrained Generative Models: A Contrastive Learning View X Ren*, T Yang*, Y Wang, W Zeng International Conference on Learning Representations (ICLR) 2022, 2021 | 46* | 2021 |
Towards Building A Group-based Unsupervised Representation Disentanglement Framework T Yang, X Ren, Y Wang, W Zeng, N Zheng International Conference on Learning Representations (ICLR) 2022, 2021 | 26* | 2021 |
Safety-aware Motion Prediction with Unseen Vehicles for Autonomous Driving X Ren*, T Yang*, EL Li, A Alexandre, Q Chen International Conference on Computer Vision (ICCV) 2021, 2021 | 21 | 2021 |
A driving behavior recognition model with bi-LSTM and multi-scale CNN H Zhang, Z Nan, T Yang, Y Liu, N Zheng 2020 IEEE Intelligent Vehicles Symposium (IV), 284-289, 2020 | 14 | 2020 |
Traffic agent trajectory prediction using social convolution and attention mechanism T Yang, Z Nan, H Zhang, S Chen, N Zheng 2020 IEEE Intelligent Vehicles Symposium (IV), 278-283, 2020 | 13 | 2020 |
Test-time Batch Normalization T Yang, S Zhou, Y Wang, Y Lu, N Zheng https://arxiv.org/abs/2205.10210, 2022 | 11 | 2022 |
DisDiff: Unsupervised Disentanglement of Diffusion Probabilistic Models T Yang, Y Wang, Y Lu, N Zheng 37th Conference on Neural Information Processing Systems (NeurIPS) 2023, 2023 | 8 | 2023 |
Rethinking Content and Style: Exploring Bias for Unsupervised Disentanglement X Ren, T Yang, Y Wang, W Zeng International Conference on Computer Vision (ICCV) Workshop, 2021 | 8 | 2021 |
Visual Concepts Tokenization T Yang, Y Wang, Y Lu, N Zheng 36th Conference on Neural Information Processing Systems (NeurIPS) 2022, 2022 | 7 | 2022 |
A Flexible Diffusion Model W Du*, T Yang*, H Zhang*, Y Du* International Conference on Machine Learning (ICML) 2023, 2022 | 5 | 2022 |
How does representation impact in-context learning: A exploration on a synthetic task J Fu*, T Yang*, Y Wang, Y Lu, N Zheng arXiv preprint arXiv:2309.06054, 2023 | 2 | 2023 |
Generalized robust test-time adaptation in continuous dynamic scenarios S Li, L Yuan, B Xie, T Yang arXiv preprint arXiv:2310.04714, 2023 | 1 | 2023 |
Vector-based Representation is the Key: A Study on Disentanglement and Compositional Generalization T Yang, Y Wang, C Lan, Y Lu, N Zheng https://arxiv.org/abs/2305.18063, 2023 | 1 | 2023 |
Activations Quantization for Compact Neural Networks Y Wei, Z Zhao, T Yang, Z Hao, P Ren 2018 IEEE 23rd International Conference on Digital Signal Processing (DSP), 1-5, 2018 | 1 | 2018 |
Closed-Loop Unsupervised Representation Disentanglement with -VAE Distillation and Diffusion Probabilistic Feedback X Jin, B Li, B Xie, W Zhang, J Liu, Z Li, T Yang, W Zeng arXiv preprint arXiv:2402.02346, 2024 | | 2024 |
Diffusion Model with Cross Attention as an Inductive Bias for Disentanglement T Yang, C Lan, Y Lu, N Zheng https://arxiv.org/abs/2402.09712.pdf, 2024 | | 2024 |
MicroCinema: A Divide-and-Conquer Approach for Text-to-Video Generation Y Wang, J Bao, W Weng, R Feng, D Yin, T Yang, J Zhang, QDZ Zhao, ... The IEEE / CVF Computer Vision and Pattern Recognition Conference (CVPR) 2024, 2023 | | 2023 |
Gradient Preserving Batch Normalization for Test-Time Adaptation T Yang, Y Wang, Y Lu, N Zheng Available at SSRN 4627328, 0 | | |