2 citations · 3 across the 6 of their papers we have counts for
4 papers · 1 filter
A Greedy PDE Router for Blending Neural Operators and Classical Methods
Sahana Rayan, Yash Patel, Ambuj Tewari
When solving PDEs, classical numerical solvers are often computationally expensive, while machine learning methods can suffer from spectral bias, failing to capture high-frequency…
Learning to Partially Defer for Sequences
Sahana Rayan, Ambuj Tewari
In the Learning to Defer (L2D) framework, a prediction model can either make a prediction or defer it to an expert, as determined by a rejector. Current L2D methods train the rejec…
Conformal Prediction for Ensembles: Improving Efficiency via Score-Based Aggregation
Eduardo Ochoa Rivera, Yash Patel, Ambuj Tewari
Distribution-free uncertainty estimation for ensemble methods is increasingly desirable due to the widening deployment of multi-modal black-box predictive models. Conformal predict…
Conformal Contextual Robust Optimization
Yash Patel, Sahana Rayan, Ambuj Tewari
Data-driven approaches to predict-then-optimize decision-making problems seek to mitigate the risk of uncertainty region misspecification in safety-critical settings. Current appro…