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arXiv:2602.00100v1 Announce Type: cross Abstract: The paper focuses on Image Compression, explaining efficient approaches based on Frequent Pattern Mining(FPM). The proposed compression mechanism is based...
arXiv:2602.00101v1 Announce Type: cross Abstract: Decentralized Finance (DeFi) has revolutionized financial markets by enabling complex asset-exchange protocols without trusted intermediaries. Automated Market Makers (AMMs) are...
arXiv:2602.00102v1 Announce Type: cross Abstract: Radiomics enables quantitative medical image analysis by converting imaging data into structured, high-dimensional feature representations for predictive modeling. Despite methodological...
arXiv:2602.00103v1 Announce Type: cross Abstract: We present an integrated multiagent AI ecosystem for polymer discovery that unifies high-throughput materials workflows, artificial intelligence, and computational modeling...
arXiv:2602.00133v1 Announce Type: cross Abstract: Prediction markets offer a natural testbed for trading agents: contracts have binary payoffs, prices can be interpreted as probabilities, and...
arXiv:2602.00136v1 Announce Type: cross Abstract: Modern Earth Observation (EO) systems increasingly rely on high-resolution imagery to support critical applications such as environmental monitoring, disaster response,...
arXiv:2602.00141v1 Announce Type: cross Abstract: We present a comprehensive comparison of convolutional and transformer-based models for distinguishing quark and gluon jets using simulated jet images...
arXiv:2602.00143v1 Announce Type: cross Abstract: Predicting critical transitions in complex systems, such as epileptic seizures in the brain, represents a major challenge in scientific research....
arXiv:2602.00157v1 Announce Type: cross Abstract: Antimicrobial resistance threatens healthcare sustainability and motivates low-cost computational discovery of antimicrobial peptides (AMPs). De novo peptide generation must optimize...
arXiv:2602.00171v1 Announce Type: cross Abstract: Multimodal learning combines information from multiple data modalities to improve predictive performance. However, modalities often contribute unequally and in a...
arXiv:2602.00172v1 Announce Type: cross Abstract: The ability of neural networks to learn useful features through stochastic gradient descent (SGD) is a cornerstone of their success....
arXiv:2602.00184v1 Announce Type: cross Abstract: Limited-angle computed tomography (LACT) offers the advantages of reduced radiation dose and shortened scanning time. Traditional reconstruction algorithms exhibit various...
arXiv:2602.00185v1 Announce Type: cross Abstract: The integration of large language models (LLMs) into materials science offers a transformative opportunity to streamline computational workflows, yet current...
arXiv:2602.00186v1 Announce Type: cross Abstract: This paper presents SurfelSoup, an end-to-end learned surface-based framework for point cloud geometry compression, with surface-structured primitives for representation. It...
arXiv:2602.00194v1 Announce Type: cross Abstract: Survival analysis deals with modeling the time until an event occurs, and accurate probability estimates are crucial for decision-making, particularly...
arXiv:2602.00197v1 Announce Type: cross Abstract: Zero-shot mutation prediction is vital for low-resource protein engineering, yet existing protein language models (PLMs) often yield statistically confident results...
arXiv:2602.00198v1 Announce Type: cross Abstract: The rapid growth in video consumption has introduced significant challenges to modern streaming architectures. Over-the-Top (OTT) video delivery now predominantly...
arXiv:2602.00201v1 Announce Type: cross Abstract: This paper implements an efficient numerical algorithm for the time-fractional Black-Scholes model governing European options. The proposed method comprises the...
arXiv:2602.00215v1 Announce Type: cross Abstract: This work focuses on assessing the information-theoretic limits of scene parameter estimation in plenoptic imaging systems. A general framework to...
arXiv:2602.00220v1 Announce Type: cross Abstract: This paper introduces a hybrid two-stage registration framework for reconstructing three-dimensional (3D) kidney anatomy from macroscopic slices, using CT-derived models...
arXiv:2602.00221v1 Announce Type: cross Abstract: Magnetic Resonance Imaging (MRI) is a crucial imaging modality for viewing internal body structures. This research work analyses the performance...
arXiv:2602.00324v1 Announce Type: cross Abstract: Synchronization over the special Euclidean group SE(3) aims to recover absolute poses from noisy pairwise relative transformations and is a...
arXiv:2602.00378v1 Announce Type: cross Abstract: We present a method for parametrizing sub-grid processes in the Shallow Water equations. We define coarse variables and local spatial...
arXiv:2602.00387v1 Announce Type: cross Abstract: Bayesian neural networks promise calibrated uncertainty but require $O(mn)$ parameters for standard mean-field Gaussian posteriors. We argue this cost is...