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arXiv:2603.06138v1 Announce Type: new Abstract: Reinforcement learning is a framework for learning to act sequentially in an unknown environment. We propose a natural approach for …
arXiv:2603.06142v1 Announce Type: new Abstract: Predictive coding graphs (PCGs) are a recently introduced generalization to predictive coding networks, a neuroscience-inspired probabilistic latent variable model. Here, …
arXiv:2603.06153v1 Announce Type: new Abstract: Accurate regional ocean forecasting requires models that are both computationally efficient and capable of representing predictive uncertainty. This work investigates …
arXiv:2603.06212v1 Announce Type: new Abstract: Differential diagnosis among parkinsonian syndromes remains a clinical challenge due to overlapping motor symptoms and subtle gait abnormalities. Accurate differentiation …
arXiv:2603.06224v1 Announce Type: new Abstract: Wearable sensors with local data processing can detect health threats early, enhance documentation, and support personalized therapy. In the context …
arXiv:2603.06242v1 Announce Type: new Abstract: Model merging aims to integrate multiple task-adapted models into a unified model that preserves the knowledge of each task. In …
arXiv:2603.06248v1 Announce Type: new Abstract: Understanding the intricate non-convex training dynamics of softmax-based models is crucial for explaining the empirical success of transformers. In this …
Recent advances in Natural Language Processing and Machine Learning provide us with the tools to build predictive models that can be used to unveil patterns …
The article is devoted to the study of the specifics of the legal regulation of the use and development of artificial intelligence for the space …