baulab.info

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David Bau: Interpretation of Deep Networks

 Generated on March 22 2026 02:59 AM

Old data? UPDATE !

The score is 63/100

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Title

David Bau: Interpretation of Deep Networks

Length : 42

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Description

Specializing in the analysis and control of the internal computations of deep generative models for images and text, David Bau is a leading researcher in interpretable deep network methods.

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Headings

H1 H2 H3 H4 H5 H6
1 4 0 0 0 0
  • [H1] David Bau
  • [H2] Lab Members
  • [H2] Current Collaborations
  • [H2] In the News
  • [H2] Selected Projects

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Anchor Type Juice
Northeastern Khoury College External Passing Juice
Apply to Khoury here External Passing Juice
contact me Internal Passing Juice
NDIF engineering fellowships External Passing Juice
Publication List Internal Passing Juice
Curriculum Vitae Internal Passing Juice
thesis External Passing Juice
Sloan fellowship External Passing Juice
Spira teaching award External Passing Juice
Dblp External Passing Juice
Google Scholar External Passing Juice
Talks at the Bau Lab Internal Passing Juice
What is AI interpretability for? Internal Passing Juice
Stata 32-383 External Passing Juice
Why nobody can see inside AI's black box External Passing Juice
How does ChatGPT think? External Passing Juice
causal tracing Internal Passing Juice
David Bau Internal Passing Juice
Mor Geva External Passing Juice
Martin Wattenberg External Passing Juice
Chris Olah External Passing Juice
Thilo Hagendorff External Passing Juice
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NSF funds groundbreaking research led by Northeastern to democratize artificial intelligence. Northeastern Global News, May 2, 2024. External Passing Juice
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Linearity of Relation Decoding in Transformer LMs. Internal Passing Juice
Fine-Tuning Enhances Existing Mechanisms. Internal Passing Juice
Wang 2022 (IOI) External Passing Juice
our DCM patching method Internal Passing Juice
Function Vectors in Large Language Models. Internal Passing Juice
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Erasing Concepts from Diffusion Models. Internal Passing Juice
classifier-free guidance External Passing Juice
Locating and Editing Factual Associations in GPT. Internal Passing Juice
Rewriting a Deep Generative Model. External Passing Juice
Understanding the Role of Individual Units in a Deep Neural Network. External Passing Juice
Structure and Interpretation of Deep Networks. External Passing Juice
Yonatan Belinkov External Passing Juice
Julius Adebayo External Passing Juice
Seeing what a GAN Cannot Generate External Passing Juice
GAN Paint External Passing Juice
GAN dissection External Passing Juice
previous work External Passing Juice
directly manipulated External Passing Juice
Network Dissection External Passing Juice
2014 finding by Bolei Zhou External Passing Juice
Blocks and Beyond External Passing Juice
also see the video overview External Passing Juice
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LinkedIn External Passing Juice
Mastodon External Passing Juice
Personal Blog External Passing Juice
Search External Passing Juice

SEO Keywords

Keywords Cloud

from gan network also models bau how deep concept model

Keywords Consistency

Keyword Content Title Keywords Description Headings
bau 27
models 25
model 23
network 21
deep 20

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Url

Domain : baulab.info

Length : 11

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