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Found 6 papers, 2 papers with code
VN-Transformer: Rotation-Equivariant Attention for Vector Neurons
Rotation equivariance is a desirable property in many practical applications such as motion forecasting and 3D perception, where it can offer benefits like sample efficiency, better generalization, and robustness to input perturbations.
Hölder Bounds for Sensitivity Analysis in Causal Reasoning
We examine interval estimation of the effect of a treatment T on an outcome Y given the existence of an unobserved confounder U.
Counterfactual Representation Learning with Balancing Weights
A key to causal inference with observational data is achieving balance in predictive features associated with each treatment type.
Double Robust Representation Learning for Counterfactual Prediction
Causal inference, or counterfactual prediction, is central to decision making in healthcare, policy and social sciences.
Enabling Counterfactual Survival Analysis with Balanced Representations
Balanced representation learning methods have been applied successfully to counterfactual inference from observational data.
Weakly Supervised Instance Learning for Thyroid Malignancy Prediction from Whole Slide Cytopathology Images
The lower bound further allows us to extend the proposed algorithm to simultaneously predict multiple bag and instance-level labels from a single output of a neural network.
