EnDfuser replaces point-estimate trajectory planning with ensemble diffusion in a single attention-pooling transformer module to model posterior trajectory uncertainty and improve safety in end-to-end autonomous driving.
Zero-shot uncer- tainty quantification using diffusion probabilistic models
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DiffUNet^2 is a bidirectional conditional diffusion model integrated with visual tools for probabilistic exploration of scientific time series across five evaluated datasets.
DAV-GSWT selects views by diffusion-model uncertainty and hallucinates missing structure so Gaussian Splatting Wang Tiles can be made from sparse captures.
citing papers explorer
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Using Ensemble Diffusion to Estimate Uncertainty for End-to-End Autonomous Driving
EnDfuser replaces point-estimate trajectory planning with ensemble diffusion in a single attention-pooling transformer module to model posterior trajectory uncertainty and improve safety in end-to-end autonomous driving.
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DiffUNet^2: Bidirectional Prediction, Probabilistic Generation and Collaborative Visual Discovery for Scientific Data
DiffUNet^2 is a bidirectional conditional diffusion model integrated with visual tools for probabilistic exploration of scientific time series across five evaluated datasets.
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DAV-GSWT: Diffusion-Active-View Sampling for Data-Efficient Gaussian Splatting Wang Tiles
DAV-GSWT selects views by diffusion-model uncertainty and hallucinates missing structure so Gaussian Splatting Wang Tiles can be made from sparse captures.