| Improving inference for neural image compression Y Yang, R Bamler, S Mandt Advances in Neural Information Processing Systems 33, 573-584, 2020 | 56 | 2020 |
| Hierarchical autoregressive modeling for neural video compression R Yang, Y Yang, J Marino, S Mandt arXiv preprint arXiv:2010.10258, 2020 | 29 | 2020 |
| An introduction to neural data compression Y Yang, S Mandt, L Theis arXiv preprint arXiv:2202.06533, 2022 | 17 | 2022 |
| Foundations of a fast, data-driven, machine-learned simulator JN Howard, S Mandt, D Whiteson, Y Yang arXiv preprint arXiv:2101.08944, 2021 | 17 | 2021 |
| Variational bayesian quantization Y Yang, R Bamler, S Mandt International Conference on Machine Learning, 10670-10680, 2020 | 16 | 2020 |
| Learning to simulate high energy particle collisions from unlabeled data JN Howard, S Mandt, D Whiteson, Y Yang Scientific reports 12 (1), 1-18, 2022 | 8 | 2022 |
| Towards empirical sandwich bounds on the rate-distortion function Y Yang, S Mandt arXiv preprint arXiv:2111.12166, 2021 | 6 | 2021 |
| Insights from Generative Modeling for Neural Video Compression R Yang, Y Yang, J Marino, S Mandt arXiv preprint arXiv:2107.13136, 2021 | 4 | 2021 |
| One-shot marginal map inference in Markov random fields H Xiong, Y Guo, Y Yang, N Ruozzi Uncertainty in Artificial Intelligence, 102-112, 2020 | 4 | 2020 |
| Lifted hybrid variational inference Y Chen, Y Yang, S Natarajan, N Ruozzi arXiv preprint arXiv:2001.02773, 2020 | 3 | 2020 |
| Scalable neural network compression and pruning using hard clustering and l1 regularization Y Yang, N Ruozzi, V Gogate arXiv preprint arXiv:1806.05355, 2018 | 3 | 2018 |
| Lower Bounding Rate-Distortion From Samples Y Yang, S Mandt Neural Compression: From Information Theory to Applications--Workshop@ ICLR 2021, 2021 | 1 | 2021 |
| The Ill-defined Problem of Maximum Likelihood Estimation Y Yang | | 2022 |
| Compressing Variational Posteriors Y Yang, R Bamler, S Mandt | | |
