Towards Regret Guarantees for One-Step Lookahead Bayesian Optimization
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New papers, breakthroughs and academic AI research
Gradient-based optimization of nuclear criticality experiments using neural surrogate eigenvalue sensitivities
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A prism hierarchy of learning regimes in large linear autoencoders
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Detecting Control and Response Events for AI-Enabled Radio Access Networks
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GRADE: Graph Representation of LLM Agent Dependency and Execution
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In-Context Residual Calibration for Uncertainty Quantification of Energy Time Series over Graphs
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Evaluating Time Series Foundation Models for Electricity Price Forecasting: Contamination Risk, Distributional Shifts, and Covariate Dependence
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Directional Curvature from Armijo Backtracking: A Low-Cost Sharpness Probe and a Calibration-Free Learning-Rate Safeguard for Adam
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Target-Guided Selective Reweighting for Physics-Informed Neural Network Inverse Problems: A Transfer Learning Approach
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Linear Independent Component Analysis via Optimal Transport
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ECGLight: Compute-Light Framework For Paper ECG Digitization and Myocardial Infarction Screening
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RUBRIC: Realism--Utility Balanced Ranking for Imbalanced Classification
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