Autovc: Zero-shot voice style transfer with only autoencoder loss K Qian, Y Zhang, S Chang, X Yang, M Hasegawa-Johnson International Conference on Machine Learning, 5210-5219, 2019 | 477 | 2019 |
The lottery ticket hypothesis for pre-trained bert networks T Chen, J Frankle, S Chang, S Liu, Y Zhang, Z Wang, M Carbin Advances in neural information processing systems 33, 15834-15846, 2020 | 353 | 2020 |
Dilated recurrent neural networks S Chang, Y Zhang, W Han, M Yu, X Guo, W Tan, X Cui, M Witbrock, ... Advances in neural information processing systems 30, 2017 | 342 | 2017 |
Invariant rationalization S Chang, Y Zhang, M Yu, T Jaakkola International Conference on Machine Learning, 1448-1458, 2020 | 205 | 2020 |
Unsupervised speech decomposition via triple information bottleneck K Qian, Y Zhang, S Chang, M Hasegawa-Johnson, D Cox International Conference on Machine Learning, 7836-7846, 2020 | 178 | 2020 |
DiffCSE: Difference-based contrastive learning for sentence embeddings YS Chuang, R Dangovski, H Luo, Y Zhang, S Chang, M Soljačić, SW Li, ... arXiv preprint arXiv:2204.10298, 2022 | 167 | 2022 |
Rethinking cooperative rationalization: Introspective extraction and complement control M Yu, S Chang, Y Zhang, TS Jaakkola arXiv preprint arXiv:1910.13294, 2019 | 146 | 2019 |
The lottery tickets hypothesis for supervised and self-supervised pre-training in computer vision models T Chen, J Frankle, S Chang, S Liu, Y Zhang, M Carbin, Z Wang Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021 | 124 | 2021 |
Streaming recommender systems S Chang, Y Zhang, J Tang, D Yin, Y Chang, MA Hasegawa-Johnson, ... Proceedings of the 26th international conference on world wide web, 381-389, 2017 | 123 | 2017 |
Fast wavenet generation algorithm TL Paine, P Khorrami, S Chang, Y Zhang, P Ramachandran, ... arXiv preprint arXiv:1611.09482, 2016 | 119 | 2016 |
Speech Enhancement Using Bayesian Wavenet. K Qian, Y Zhang, S Chang, X Yang, D Florêncio, M Hasegawa-Johnson Interspeech, 2013-2017, 2017 | 101 | 2017 |
Fast generation for convolutional autoregressive models P Ramachandran, TL Paine, P Khorrami, M Babaeizadeh, S Chang, ... arXiv preprint arXiv:1704.06001, 2017 | 81 | 2017 |
Generating visually aligned sound from videos P Chen, Y Zhang, M Tan, H Xiao, D Huang, C Gan IEEE Transactions on Image Processing 29, 8292-8302, 2020 | 80 | 2020 |
Contentvec: An improved self-supervised speech representation by disentangling speakers K Qian, Y Zhang, H Gao, J Ni, CI Lai, D Cox, M Hasegawa-Johnson, ... International Conference on Machine Learning, 18003-18017, 2022 | 70 | 2022 |
A game theoretic approach to class-wise selective rationalization S Chang, Y Zhang, M Yu, T Jaakkola Advances in neural information processing systems 32, 2019 | 63 | 2019 |
Uncovering the disentanglement capability in text-to-image diffusion models Q Wu, Y Liu, H Zhao, A Kale, T Bui, T Yu, Z Lin, Y Zhang, S Chang Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 58 | 2023 |
Parp: Prune, adjust and re-prune for self-supervised speech recognition CIJ Lai, Y Zhang, AH Liu, S Chang, YL Liao, YS Chuang, K Qian, ... Advances in Neural Information Processing Systems 34, 21256-21272, 2021 | 58 | 2021 |
Deep learning based speech beamforming K Qian, Y Zhang, S Chang, X Yang, D Florencio, M Hasegawa-Johnson 2018 IEEE International Conference on Acoustics, Speech and Signal …, 2018 | 44 | 2018 |
Positive-Unlabeled Learning in Streaming Networks. S Chang, Y Zhang, J Tang, D Yin, Y Chang, MA Hasegawa-Johnson, ... KDD, 755-764, 2016 | 42 | 2016 |
Understanding interlocking dynamics of cooperative rationalization M Yu, Y Zhang, S Chang, T Jaakkola Advances in Neural Information Processing Systems 34, 12822-12835, 2021 | 36 | 2021 |