4 citations · 9 across the 5 of their papers we have counts for
5 papers
Ablation Based Counterfactuals
Zheng Dai, David K Gifford
Diffusion models are a class of generative models that generate high-quality samples, but at present it is difficult to characterize how they depend upon their training data. This…
Measuring the Success of Diffusion Models at Imitating Human Artists
Stephen Casper, Zifan Guo, Shreya Mogulothu +5
Modern diffusion models have set the state-of-the-art in AI image generation. Their success is due, in part, to training on Internet-scale data which often includes copyrighted wor…
Training Data Attribution for Diffusion Models
Zheng Dai, David K Gifford
Diffusion models have become increasingly popular for synthesizing high-quality samples based on training datasets. However, given the oftentimes enormous sizes of the training dat…
Constrained Submodular Optimization for Vaccine Design
Zheng Dai, David Gifford
Advances in machine learning have enabled the prediction of immune system responses to prophylactic and therapeutic vaccines. However, the engineering task of designing vaccines re…
Image classifiers can not be made robust to small perturbations
Zheng Dai, David K. Gifford
The sensitivity of image classifiers to small perturbations in the input is often viewed as a defect of their construction. We demonstrate that this sensitivity is a fundamental pr…