Statistical Learning
On Inductive Biases for Heterogeneous Treatment Effect Estimation
We investigate how to exploit structural similarities of an individual's potential
Motif-based Graph Self-Supervised Learning for Molecular Property Prediction
To bridge this gap, we propose Motif-based Graph Self-supervised Learning (MGSSL) by introducing a novel self-supervised motif generation framework for GNNs.
Extended benchmarks and implementations Content of the supplementary materials
We now discuss the applications of symbolic tensors to clustering.
Fast geometric learning with symbolic matrices Jean Feydy
We perform an extensive evaluation on a broad class of problems: Gaussian modelling, K-nearest neighbors search, geometric deep learning, non-Euclidean embeddings and optimal transport theory.
Doubly Robust Thompson Sampling with Linear Payoffs
Contextual bandit has been popular in sequential decision tasks such as news article recommendation systems. In bandit problems, the learner sequentially pulls one arm among multiple arms and receives random rewards on each round of time.