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DiffM2A achieves superior Ambisonic encoding fidelity, maintaining performance across diverse microphone configurations and boundary conditions.
Exact boundary enforcement in PINNs isn't enough; the choice of distance function can make or break the accuracy of solutions to elliptic Dirichlet problems.
SST-CD filters out noise in temporal discrepancies to achieve state-of-the-art performance in unsupervised building change detection.
Forget painstakingly tuning time steps: this generative method learns Wasserstein gradient flows with stable training, achieving high accuracy with only a handful of discretization points.
MRI reconstruction can be made dramatically more robust to clinical domain shifts by eliminating the need for explicit coil sensitivity map estimation.
Sports expose surprising limitations in VLMs' spatial reasoning, as current models struggle to generalize from existing benchmarks despite fine-tuning gains on a new, large-scale dataset.
