2 citations · 2 across the 5 of their papers we have counts for
3 papers · 1 filter
Conditional Flow Models Convert Epistemic Uncertainty into Apparent Aleatoric Variance
Navodita Sharma, Abhishek Shetty, Max Simchowitz +1
Conditional Flow Models (CFMs) are increasingly being used in place of deterministic predictors across machine learning, including for tasks that were classically formulated as reg…
Learning with Monotone Adversarial Corruptions
Kasper Green Larsen, Chirag Pabbaraju, Abhishek Shetty
We study the extent to which standard machine learning algorithms rely on exchangeability and independence of data by introducing a monotone adversarial corruption model. In this m…
Progressive Ensemble Distillation: Building Ensembles for Efficient Inference
Don Kurian Dennis, Abhishek Shetty, Anish Sevekari +2
We study the problem of progressive ensemble distillation: Given a large, pretrained teacher model , we seek to decompose the model into smaller, low-inference cost student mode…