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arXiv:2603.03344v1 Announce Type: cross Abstract: Earthquake detection and seismic phase picking are fundamental yet challenging tasks in seismology due to low signal-to-noise ratios, waveform variability,...
arXiv:2603.03346v1 Announce Type: cross Abstract: Modeling the unsaturated behavior of porous materials with multimodal pore size distributions presents significant challenges, as standard hydraulic models often...
arXiv:2603.03350v1 Announce Type: cross Abstract: Manual measurement of muscle morphology from ultrasound during speech is time-consuming and limits large-scale studies. We present SMMA, a fully...
arXiv:2603.03352v1 Announce Type: cross Abstract: The International Physics Olympiad (IPhO) is the world's most prestigious and renowned physics competition for pre-university students. IPhO problems require...
arXiv:2603.03354v1 Announce Type: cross Abstract: Although obtaining deep brain activity from non-invasive scalp electroencephalography (sEEG) is crucial for neuroscience and clinical diagnosis, directly generating high-fidelity...
arXiv:2603.03355v1 Announce Type: cross Abstract: We present a memory-augmented transformer in which attention serves simultaneously as a retrieval, consolidation, and write-back operator. The core update,...
arXiv:2603.03366v1 Announce Type: cross Abstract: We consider the implementation of optimization techniques within the study of tectonic plate motion. Specifically, we examine the optimization underlying...
arXiv:2603.03372v1 Announce Type: cross Abstract: Density Functional Theory (DFT) is a cornerstone of materials science, yet executing DFT in practice requires coordinating a complex, multi-step...
arXiv:2603.03375v1 Announce Type: cross Abstract: In 2018, McInnes et al. introduced a dimensionality reduction algorithm called UMAP, which enjoys wide popularity among data scientists. Their...
arXiv:2603.03387v1 Announce Type: cross Abstract: Clustering is a fundamental approach to understanding data patterns, wherein the intuitive Euclidean distance space is commonly adopted. However, this...
arXiv:2603.03401v1 Announce Type: cross Abstract: This paper proposes a novel parameter selection strategy for kernel-based gradient descent (KGD) algorithms, integrating bias-variance analysis with the splitting...
arXiv:2603.03405v1 Announce Type: cross Abstract: The forward and reverse Kullback-Leibler (KL) divergences arise as limiting objectives in learning and inference yet induce markedly different inductive...
arXiv:2603.03411v1 Announce Type: cross Abstract: Observational causal discovery is only identifiable up to the Markov equivalence class. While interventions can reduce this ambiguity, in practice...
arXiv:2603.03476v1 Announce Type: cross Abstract: We propose a novel computational framework for analyzing electroencephalography (EEG) time series using methods from stringology, the study of efficient...
arXiv:2603.03493v1 Announce Type: cross Abstract: Benchmark rankings are routinely used to justify scientific claims about method quality in gene regulatory network (GRN) inference, yet the...
arXiv:2603.03587v1 Announce Type: cross Abstract: Method validation and study design in causal inference rely on synthetic data with known counterfactuals. Existing simulators trade off distributional...
arXiv:2603.03613v1 Announce Type: cross Abstract: The No Free Lunch (NFL) theorem guarantees equal average performance only under uniform sampling of a function space closed under...
arXiv:2603.03626v1 Announce Type: cross Abstract: Low-dimensional structure in real-world data plays an important role in the success of generative models, which motivates diffusion models defined...
arXiv:2603.03641v1 Announce Type: cross Abstract: Rapid urban population growth drives car travel demand, increasing transport carbon emissions and posing a critical challenge to sustainable development....
arXiv:2603.03682v1 Announce Type: cross Abstract: Accurate polyp segmentation is essential for early colorectal cancer detection, yet achieving reliable boundary localization remains challenging due to low...
arXiv:2603.03684v1 Announce Type: cross Abstract: Recent developments show that AI can prove research-level theorems in mathematics, both formally and informally. This essay urges mathematicians to...
arXiv:2603.03700v1 Announce Type: cross Abstract: Despite the remarkable empirical success of score-based diffusion models, their statistical guarantees remain underdeveloped. Existing analyses often provide pessimistic convergence...
arXiv:2603.03785v1 Announce Type: cross Abstract: Randomized Controlled Trials (RCTs) represent the gold standard for causal inference yet remain a scarce resource. While large-scale observational data...
arXiv:2603.03832v1 Announce Type: cross Abstract: Cardiac arrhythmogenesis is governed by complex electromechanical interactions that are not directly observable in vivo, motivating the development of non-invasive...