Numerical linear algebra LN Trefethen, D Bau Society for Industrial and Applied Mathematics, 2022 | 6994 | 2022 |
Proceedings of the IEEE conference on computer vision and pattern recognition K He, X Zhang, S Ren, J Sun | 4171 | 2016 |
Explaining explanations: An overview of interpretability of machine learning LH Gilpin, D Bau, BZ Yuan, A Bajwa, M Specter, L Kagal 2018 IEEE 5th International Conference on data science and advanced …, 2018 | 2843 | 2018 |
Network dissection: Quantifying interpretability of deep visual representations D Bau, B Zhou, A Khosla, A Oliva, A Torralba Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 1679 | 2017 |
Locating and editing factual associations in GPT K Meng, D Bau, A Andonian, Y Belinkov Advances in Neural Information Processing Systems 35, 17359-17372, 2022 | 649* | 2022 |
GAN Dissection: Visualizing and Understanding Generative Adversarial Networks D Bau, JY Zhu, H Strobelt, B Zhou, JB Tenenbaum, WT Freeman, ... International Conference on Learning Representations (ICLR 2019), 2019 | 578 | 2019 |
Understanding the role of individual units in a deep neural network D Bau, JY Zhu, H Strobelt, A Lapedriza, B Zhou, A Torralba Proceedings of the National Academy of Sciences 117 (48), 30071-30078, 2020 | 444 | 2020 |
Determining advertisements using user behavior information such as past navigation information D Bau US Patent App. 10/955,828, 2006 | 382 | 2006 |
Learnable programming: blocks and beyond D Bau, J Gray, C Kelleher, J Sheldon, F Turbak Communications of the ACM 60 (6), 72-80, 2017 | 368 | 2017 |
Semantic photo manipulation with a generative image prior D Bau, H Strobelt, W Peebles, J Wulff, B Zhou, JY Zhu, A Torralba arXiv preprint arXiv:2005.07727, 2020 | 356 | 2020 |
Seeing what a gan cannot generate D Bau, JY Zhu, J Wulff, W Peebles, H Strobelt, B Zhou, A Torralba Proceedings of the IEEE/CVF international conference on computer vision …, 2019 | 347 | 2019 |
Interpreting deep visual representations via network dissection B Zhou, D Bau, A Oliva, A Torralba IEEE transactions on pattern analysis and machine intelligence 41 (9), 2131-2145, 2018 | 347 | 2018 |
Interpretable basis decomposition for visual explanation B Zhou, Y Sun, D Bau, A Torralba Proceedings of the European Conference on Computer Vision (ECCV), 119-134, 2018 | 335 | 2018 |
What makes fake images detectable? understanding properties that generalize L Chai, D Bau, SN Lim, P Isola Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020 | 273 | 2020 |
Mass-editing memory in a transformer K Meng, AS Sharma, A Andonian, Y Belinkov, D Bau The Eleventh International Conference on Learning Representations (ICLR 2022), 2022 | 264 | 2022 |
Providing images of named resources in response to a search query D Bau, G Erkan, OA Osman, SA Safier, CYC Lo US Patent 9,026,526, 2015 | 216 | 2015 |
Annotation based development platform for stateful web services D Bau III, A Bosworth, GS Burd, RA Chavez, KW Marvin US Patent 7,437,710, 2008 | 210 | 2008 |
Systems and methods for creating network-based software services using source code annotations K Marvin, D Remy, D Bau, RA Chavez, D Read US Patent 7,707,564, 2010 | 177 | 2010 |
Pencil code: block code for a text world D Bau, DA Bau, M Dawson, CS Pickens Proceedings of the 14th international conference on interaction design and …, 2015 | 153 | 2015 |
Emergent world representations: Exploring a sequence model trained on a synthetic task K Li, AK Hopkins, D Bau, F Viégas, H Pfister, M Wattenberg The Eleventh International Conference on Learning Representations (ICLR 2022), 2022 | 152 | 2022 |