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Natural image matting is the task of precisely estimating alpha mattes to separate foreground objects from background images. Existing …
The artificial intelligence research community is continuing to grapple with the ethics of their work by encouraging researchers to …
We study settings where gradient penalties are used alongside risk minimization with the goal of obtaining predictors satisfying …
Rapid development of large-scale pre-training has resulted in foundation models that can act as effective feature extractors on a …
The standard formulation of Reinforcement Learning lacks a practical way of specifying what are admissible and forbidden behaviors. …
The estimation of time-varying quantities is a fundamental component of decision making in fields such as healthcare and finance. …
Data is the driving force of machine learning, with the amount and quality of training data often being more important for the …
Transfer learning from large-scale pre-trained models has become essential for many computer vision tasks. Recent studies have shown …
We introduce Neural Point Light Fields that represent scenes implicitly with a light field living on a sparse point cloud. Combining …
Counterfactual prediction under sequences of actions is a fundamental problem in decision-making. Existing methods in causal inference …