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arXiv:2603.20266v1 Announce Type: new Abstract: Despite the rapid advancements in Artificial Intelligence (AI), Stochastic Differential Equations (SDEs) remain the gold-standard formalism for modeling systems under …
arXiv:2603.20295v1 Announce Type: new Abstract: Uncovering causal structures from observational data is crucial for understanding complex systems and making informed decisions. While reinforcement learning (RL) …
arXiv:2603.20296v1 Announce Type: new Abstract: Recent advances in collaborative knowledge distillation have demonstrated cutting-edge performance for resource-constrained distributed multimedia learning scenarios. However, achieving such competitiveness …
arXiv:2603.20297v1 Announce Type: new Abstract: Accurate calibration is essential for instruments whose measurements must remain traceable, reliable, and compliant over long operating periods. Fixed-interval programs …
arXiv:2603.20315v1 Announce Type: new Abstract: (a) Many air quality forecasting studies report gains from machine learning, but evaluations often use static chronological splits and omit …
arXiv:2603.20327v1 Announce Type: new Abstract: Video world models trained with Joint Embedding Predictive Architectures (JEPA) acquire rich spatiotemporal representations by predicting masked regions in latent …
arXiv:2603.20333v1 Announce Type: new Abstract: Modern autonomous multi-agent systems combine heterogeneous learning mechanisms operating at different timescales. An open question remains: can one formally guarantee …
arXiv:2603.20335v1 Announce Type: new Abstract: The Interest Public Group ARRONAX's C70XP cyclotron, used for radioisotope production for medical and research applications, relies on complex and …
arXiv:2603.20339v1 Announce Type: new Abstract: Many learning systems now use graph data in which each node also contains text, such as papers with abstracts or …
arXiv:2603.20341v1 Announce Type: new Abstract: Machine learning (ML) promises better clinical decision-making, yet opaque model behavior limits the adoption in healthcare. We propose two novel …
arXiv:2603.20352v1 Announce Type: new Abstract: Time series machine learning (TSML) is a growing research field that spans a wide range of tasks. The popularity of …
arXiv:2603.20390v1 Announce Type: new Abstract: Cooperative multi-agent reinforcement learning (c-MARL) has been widely deployed in real-world applications, such as social robots, embodied intelligence, UAV swarms, …