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Found 6 papers, 2 papers with code
Plasma Surrogate Modelling using Fourier Neural Operators
Predicting plasma evolution within a Tokamak reactor is crucial to realizing the goal of sustainable fusion.
Causal Inference with Treatment Measurement Error: A Nonparametric Instrumental Variable Approach
We propose a kernel-based nonparametric estimator for the causal effect when the cause is corrupted by error.
Stochastic Causal Programming for Bounding Treatment Effects
Causal effect estimation is important for many tasks in the natural and social sciences.
Counterfactual Data Augmentation for Neural Machine Translation
We propose a data augmentation method for neural machine translation.
Learning Binary Trees via Sparse Relaxation
In this work we derive a novel sparse relaxation for binary tree learning.
Pre-Training by Completing Point Clouds
There has recently been a flurry of exciting advances in deep learning models on point clouds.
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