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Ditch the slow per-scene optimization: SwiftGS meta-learns transferable priors for satellite surface reconstruction, enabling single-pass 3D recovery.
LiveGraph tackles the cold-start problem in exercise recommendation by actively constructing a graph that connects active and inactive students, leading to improved accuracy and diversity.
SubQuad tackles the computational bottleneck of adaptive immune repertoire analysis with a near-quadratic-free approach that also corrects for dataset imbalances, enabling more equitable and scalable biomarker discovery.
Achieve practical privacy-utility trade-offs in multimodal sentiment analysis with Missing-by-Design (MBD), a framework that surgically removes modality-specific information without full retraining.
By actively exploring knowledge graphs with a differentiable neural-symbolic approach, NeuroSymActive achieves strong KGQA accuracy while drastically reducing the computational cost of graph lookups.
Generate expansive, high-fidelity 3D environments with Gaussian Splatting using significantly less data by intelligently sampling viewpoints and hallucinating details with diffusion models.
