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:::info Astounding Stories of Super-Science April 2004, by Astounding Stories is part of HackerNoon’s Book Blog Post series. You can jump to any chapter in this book here. THE COUNTRY OF THE BLIND – VII. — THE REMARKABLE CASE OF DAVIDSON’S EYES. Astounding Stories of Super-Science April 2004: THE COUNTRY OF THE BLIND – VII. — THE REMARKABLE CASE OF DAVIDSON’S EYES. By H. G. Wells ::: I. — The transitory mental aberration of Sidney Davidson, remarkable enough in […]

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Many safety-critical scientific and engineering systems evolve according to differential-algebraic equations (DAEs), where dynamical behavior is constrained by physical laws and admissibility conditions. In practice, these systems operate under stochastically varying environmental inputs, so stability is not a static property but must be reassessed as the context distribution shifts. Repeated large-scale DAE simulation, however, is computationally prohibitive in high-dimensional or real-time settings. This paper proposes a test-oriented learning framework for stability assessment under distribution shift. Rather than re-estimating […]

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Data leakage remains a recurrent source of optimistic bias in biomedical machine learning studies. Standard row-wise cross-validation and globally estimated preprocessing steps are often inappropriate for data with repeated measurements, study-level heterogeneity, batch effects, or temporal dependencies. This paper describes bioLeak, an R package for constructing leakage-aware resampling workflows and for auditing fitted models for common leakage mechanisms. The package provides leakage-aware split construction, train-fold-only preprocessing, cross-validated model fitting, nested hyperparameter tuning, post hoc leakage audits, and HTML […]

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Author(s): Gaurav Yadav Originally published on Towards AI. Anthropic shipped Managed Agents this week. AWS Bedrock AgentCore has been GA for five months. The interesting question isn’t who wins the runtime — it’s where the value migrates when the layer goes flat. On April 8, Anthropic launched the public beta of Claude Managed Agents. The launch coverage hit the predictable beats: ten-times-faster shipping, Notion and Asana as adopters, sandboxed execution and checkpointed sessions and credentialed tool calls handled […]

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arXiv:2604.08722v1 Announce Type: new Abstract: Sport analysis is crucial for team performance since it provides actionable data that can inform coaching decisions, improve player performance, and enhance team strategies. To analyze more complex features from game footage, a computer vision model can be used to identify and track key entities from the field. We propose the use of an object detection and tracking system to predict player positioning throughout the game. To translate this to positioning in relation […]

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arXiv:2604.08721v1 Announce Type: new Abstract: This paper studies stabilization and its corresponding closed-loop region-of-attraction (ROA) for homogeneous polynomial dynamical systems whose nonlinear term admits an orthogonally decomposable (ODECO) tensor representation. While recent tensor-based results provide explicit solutions and sharp global characterizations for open-loop ODECO systems, closed-loop synthesis and computable ROA estimates are still often dominated by local linearization or Lyapunov/SOS (sum of squares) methods, which can be conservative and computationally demanding. We propose a structure-preserving linear feedback design […]

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arXiv:2604.08720v1 Announce Type: new Abstract: Performance optimization of AI infrastructure is key to the fast adoption of large language models (LLMs). The PyTorch compiler (torch.compile), a core optimization tool for deep learning (DL) models (including LLMs), has received due attention. However, torch.compile is prone to correctness bugs, which cause incorrect outputs of compiled DL models without triggering exceptions, crashes, or warnings. These bugs pose a serious threat to the reliability of downstream LLM applications. Data from the PyTorch […]

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