3 citations · 5 across the 12 of their papers we have counts for
4 papers · 1 filter
Finetuning CLIP to Reason about Pairwise Differences
Dylan Sam, Devin Willmott, Joao D. Semedo +1
Vision-language models (VLMs) such as CLIP are trained via contrastive learning between text and image pairs, resulting in aligned image and text embeddings that are useful for man…
Computing Low-Entropy Couplings for Large-Support Distributions
Samuel Sokota, Dylan Sam, Christian Schroeder de Witt +3
Minimum-entropy coupling (MEC) -- the process of finding a joint distribution with minimum entropy for given marginals -- has applications in areas such as causality and steganogra…
Auditing Fairness under Unobserved Confounding
Yewon Byun, Dylan Sam, Michael Oberst +2
Many definitions of fairness or inequity involve unobservable causal quantities that cannot be directly estimated without strong assumptions. For instance, it is particularly diffi…
Bayesian Neural Networks with Domain Knowledge Priors
Dylan Sam, Rattana Pukdee, Daniel P. Jeong +2
Bayesian neural networks (BNNs) have recently gained popularity due to their ability to quantify model uncertainty. However, specifying a prior for BNNs that captures relevant doma…