These skills are refined and updated through an iterative comparison strategy, enabling efficient adaptation to unseen environments.

In this work, we propose InteractTraj, the first language-driven traffic trajectory generator that can generate interactive traffic trajectories.

The Appendix is structured as follows: We provide a proof of conditional guarantees in EENNs for (hard) PoE in Appendix A . We conduct an ablation study for our P A model in Appendix B.2 . We report results of NLP experiments in Appendix B.4 . We discuss anytime regression and deep ensembles in Appendix B.6 . We propose a technique for controlling the violations of conditional monotonicity in P A in Appendix B.8 .

Synthetic face recognition (SFR) aims to generate synthetic face datasets that mimic the distribution of real face data, which allows for training face recognition models in a privacy-preserving manner.

The authors contributed equally to this work 37th Conference on Neural Information Processing Systems (NeurIPS 2023). Developing upper bounds on the generalisation gap, i.e., generalisation bounds has been a longstanding topic in statistical learning.

Unsupervised skill discovery carries the promise that an intelligent agent can learn reusable skills through autonomous, reward-free environment interaction.