21 papers
SR-OPSD: Self-Referenced On-Policy Self-Distillation
Zhuo Sun, Entong Li, Yanlong Zhao +7
On-policy self-distillation (OPSD) converts feedback into dense token-level supervision on trajectories generated by the policy to be optimized, providing a useful complement to re…
From Deterministic to Generative Deep Learning for Urban Air Quality Reconstruction from Sparse Observations
Abhishek A. Sabnis, Mihai Mitrea, Lya Lugon +5
Full-field reconstruction of air pollution is essential for evaluating pollution exposure and supporting public health decision-making. However, the complex interactions among poll…
A Gradient Flow Perspective on Minimum MMD Estimation
Sophia Seulkee Kang, Louis Sharrock, Xiaoyuan Cheng +2
Minimum maximum mean discrepancy (MMD) estimation has emerged as a robust and likelihood-free alternative to maximum likelihood estimation for parameter estimation. Yet, despite it…
NEUROSYMLAND: Neuro-Symbolic Landing-Site Assessment for Robust and Edge-Deployable UAV Autonomy
Weixian Qian, Tianyi Yang, Sebastian Schroder +5
Safe landing-site assessment in unstructured environments remains a key challenge for autonomous UAV deployment, as vision-only learning approaches often degrade under terrain vari…
Scaling World-Model Reinforcement Learning Through Diffusion Policy Optimization
Xiaoyuan Cheng, Wenxuan Yuan, Zhancun Mu +5
Model-based reinforcement learning (RL) can be effectively supported at scale through the use of world models. However, in practice, scaling such approaches remains fundamentally l…
Outlier-robust Diffusion Posterior Sampling for Bayesian Inverse Problems
Yiming Yang, Xiaoyuan Cheng, Yi He +3
Diffusion models have emerged as powerful learned priors for Bayesian inverse problems (BIPs). Diffusion-based solvers rely on a presumed likelihood for the observations in BIPs to…