David Bau - researchr alias

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Viewing Publication 1 - 41 from 41

2023

Emergent World Representations: Exploring a Sequence Model Trained on a Synthetic TaskKenneth Li 0002, Aspen K. Hopkins, David Bau, Fernanda B. Viégas, Hanspeter Pfister, Martin Wattenberg. iclr 2023: [doi]

Erasing Concepts from Diffusion ModelsRohit Gandikota, Joanna Materzynska, Jaden Fiotto-Kaufman, David Bau. iccv 2023: 2426-2436 [doi]

Testing methods of neural systems understandingGrace W. Lindsay, David Bau. cogsr, 82:101156, December 2023. [doi]

Content-based Search for Deep Generative ModelsDaohan Lu, Sheng-yu Wang, Nupur Kumari, Rohan Agarwal, Mia Tang, David Bau, Jun-Yan Zhu. siggrapha 2023: [doi]

Mass-Editing Memory in a TransformerKevin Meng, Arnab Sen Sharma, Alex J. Andonian, Yonatan Belinkov, David Bau. iclr 2023: [doi]

Future Lens: Anticipating Subsequent Tokens from a Single Hidden StateKoyena Pal, Jiuding Sun, Andrew Yuan, Byron C. Wallace, David Bau. conll 2023: 548-560 [doi]

Multimodal Neurons in Pretrained Text-Only TransformersSarah Schwettmann, Neil Chowdhury, Samuel Klein, David Bau, Antonio Torralba 0001. iccvw 2023: 2854-2859 [doi]

FIND: A Function Description Benchmark for Evaluating Interpretability MethodsSarah Schwettmann, Tamar Rott Shaham, Joanna Materzynska, Neil Chowdhury, Shuang Li, Jacob Andreas, David Bau, Antonio Torralba 0001. nips 2023: [doi]

2022

2021

From Droplet to Lilypad: Present and Future of Dual-Modality EnvironmentsEmma Andrews, David Bau, Jeremiah J. Blanchard. vl 2021: 1-2 [doi]

Dissection of Deep Neural NetworksDavid Bau. PhD thesis, Massachusetts Institute of Technology, USA, 2021. [doi]

Editing a classifier by rewriting its prediction rulesShibani Santurkar, Dimitris Tsipras, Mahalaxmi Elango, David Bau, Antonio Torralba 0001, Aleksander Madry. nips 2021: 23359-23373 [doi]

Toward a Visual Concept Vocabulary for GAN Latent SpaceSarah Schwettmann, Evan Hernandez, David Bau, Samuel Klein, Jacob Andreas, Antonio Torralba 0001. iccv 2021: 6784-6792 [doi]

Sketch Your Own GANSheng-yu Wang, David Bau, Jun-Yan Zhu. iccv 2021: 14030-14040 [doi]

2020

2019

GAN Dissection: Visualizing and Understanding Generative Adversarial NetworksDavid Bau, Jun-Yan Zhu, Hendrik Strobelt, Bolei Zhou, Joshua B. Tenenbaum, William T. Freeman, Antonio Torralba 0001. iclr 2019: [doi]

Seeing What a GAN Cannot GenerateDavid Bau, Jun-Yan Zhu, Jonas Wulff, William S. Peebles, Bolei Zhou, Hendrik Strobelt, Antonio Torralba 0001. iccv 2019: 4501-4510 [doi]

Visualizing and Understanding GANsDavid Bau, Jun-Yan Zhu, Hendrik Strobelt, Bolei Zhou, Joshua B. Tenenbaum, William T. Freeman, Antonio Torralba 0001. iclr 2019: [doi]

Semantic photo manipulation with a generative image priorDavid Bau, Hendrik Strobelt, William S. Peebles, Jonas Wulff, Bolei Zhou, Jun-Yan Zhu, Antonio Torralba 0001. tog, 38(4), 2019. [doi]

Learning Words by Drawing ImagesDidac Suris, Adrià Recasens, David Bau, David Harwath, James R. Glass, Antonio Torralba 0001. cvpr 2018: 2029-2038 [doi]

The cloud is the limit: A case study of programming on the web, with the webDavid Weintrop, David Bau, Uri Wilensky. ijcci, 20:1-8, 2019. [doi]

Comparing the Interpretability of Deep Networks via Network DissectionBolei Zhou, David Bau, Aude Oliva, Antonio Torralba 0001. In Wojciech Samek, Grégoire Montavon, Andrea Vedaldi, Lars Kai Hansen, Klaus-Robert Müller, editors, Explainable AI: Interpreting, Explaining and Visualizing Deep Learning. Volume 11700 of Lecture Notes in Computer Science, pages 243-252, Springer, 2019. [doi]

Interpreting Deep Visual Representations via Network DissectionBolei Zhou, David Bau, Aude Oliva, Antonio Torralba 0001. pami, 41(9):2131-2145, 2019. [doi]

2018

Explaining Explanations: An Overview of Interpretability of Machine LearningLeilani H. Gilpin, David Bau, Ben Z. Yuan, Ayesha Bajwa, Michael Specter, Lalana Kagal. dsaa 2018: 80-89 [doi]

Interpretable Basis Decomposition for Visual ExplanationBolei Zhou, Yiyou Sun, David Bau, Antonio Torralba 0001. eccv 2018: 122-138 [doi]

2017

Learnable programming: blocks and beyondDavid Bau, Jeff Gray, Caitlin Kelleher, Josh Sheldon, Franklyn Turbak. CACM, 60(6):72-80, 2017. [doi]

Network Dissection: Quantifying Interpretability of Deep Visual RepresentationsDavid Bau, Bolei Zhou, Aditya Khosla, Aude Oliva, Antonio Torralba 0001. cvpr 2017: 3319-3327 [doi]

2015

2008

Large scale learning and recognition of faces in web videosMing Zhao, Jay Yagnik, Hartwig Adam, David Bau. fgr 2008: 1-7 [doi]

2001

Solving Alignment Using Elementary Linear AlgebraVladimir Kotlyar, David Bau, Induprakas Kodukula, Keshav Pingali, Paul Stodghill. cosps 2001: 385-412 [doi]

1997

Numerical linear algebraLloyd N. Trefethen, David Bau. SIAM, 1997.

1994

Solving Alignment Using Elementary Linear AlgebraDavid Bau, Induprakas Kodukula, Vladimir Kotlyar, Keshav Pingali, Paul Stodghill. lcpc 1995: 46-60

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1994

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