R-U-SURE? Uncertainty-Aware Code Suggestions By Maximizing Utility Across Random User Intents

LegendreTron: Uprising Proper Multiclass Loss Learning

Determinantal Point Process Likelihoods for Sequential Recommendation

EditVAE: Unsupervised Part-Aware Controllable 3D Point Cloud Shape Generation

TacticZero: Learning to Prove Theorems from Scratch with Deep Reinforcement Learning

All your loss are belong to Bayes

Quantile Propagation for Wasserstein-Approximate Gaussian Processes

Variational Inference for Sparse Gaussian Process Modulated Hawkes Process

Efficient non-parametric Bayesian Hawkes processes

Monge blunts Bayes: Hardness results for adversarial training