Dave Epstein.

Toggle dark mode. Scholar. CV. Pixels. dave [at] eecs.berkeley.edu.
I am a fourth-year PhD student at Berkeley AI Research advised by Alexei Efros and currently a student researcher at Google.
My research is in unsupervised deep learning,
with a focus on discovering emergent structure in visual generative models. I also work on designing scalable architectures and objectives that facilitate this goal.
In the past, I have been fortunate to collaborate with Taesung Park, Richard Zhang, and Eli Shechtman at Adobe, as well as with Chen Sun, Jiajun Wu, and Cordelia Schmid at Google. Before that, I graduated from Columbia with a BS in computer science, where I was lucky to be introduced to machine learning and advised by Carl Vondrick. My research is supported by the PD Soros Fellowship.

Research.
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Diffusion Self-Guidance for Controllable Image Generation.
Dave Epstein, Allan Jabri, Ben Poole, Alexei A. Efros, Aleksander Holynski.
PaperProject Page Talk Demo
NeurIPS 2023. -
BlobGAN: Spatially Disentangled Scene Representations. NEW!
Dave Epstein, Taesung Park, Richard Zhang, Eli Shechtman, Alexei A. Efros.
PaperProject Page Talk Code Demo
ECCV 2022. -
Globetrotter: Unsupervised Multilingual Translation from Visual Alignment. NEW!
Didac Suris, Dave Epstein, Carl Vondrick.
PaperProject Page
CVPR 2022 (Oral). -
Learning Temporal Dynamics from Cycles in Narrated Video.
Dave Epstein, Jiajun Wu, Cordelia Schmid, Chen Sun.
PaperProject Page Talk Blogpost
ICCV 2021. -
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Learning to Learn Words from Visual Scenes.
Didac Suris*, Dave Epstein*, Heng Ji, Shih-Fu Chang, Carl Vondrick
PaperProject PageTalk
ECCV 2020. -
Oops! Predicting Unintentional Action in Video.
Dave Epstein, Boyuan Chen, Carl Vondrick.
PaperProject PageTalk
CVPR 2020.
Teaching.
At Columbia.
Head Teaching Assistant.
Head Teaching Assistant.