split conformal prediction
PulseAugur coverage of split conformal prediction — every cluster mentioning split conformal prediction across labs, papers, and developer communities, ranked by signal.
3 day(s) with sentiment data
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New method maps transonic flutter boundary with active learning
Researchers have developed a new method for mapping the transonic flutter boundary of airfoils, specifically focusing on Isogai's case A. This method utilizes coupled unsteady Euler simulations and a Gaussian-process su…
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Maintaining Conformal Prediction Guarantees Amidst Data Shifts
Split conformal prediction offers coverage guarantees for model predictions, but these guarantees degrade when the underlying data distribution shifts over time. Practitioners face challenges in maintaining these guaran…
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New Conformal Prediction Method Tackles Spatially Dependent Data
Researchers have developed a new method for conformal prediction designed to handle spatially dependent data, which is common in environmental and geographical applications. This technique, called sequential whitening, …
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New research tackles data shift in conformal prediction methods
Two new research papers explore advanced conformal prediction techniques for handling data shifts. The first paper introduces Multi-Source Randomly Localized Conformal Prediction (MS-RLCP) to leverage complementary info…
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New MUSIC-Net framework enhances near-field multi-user positioning with deep learning and conformal prediction
Researchers have developed MUSIC-Net, a deep learning framework for precise near-field multi-user positioning in wireless systems. This framework integrates a two-stage MUltiple SIgnal Classification (MUSIC) approach to…
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New research quantifies cost of per-class coverage under distribution shift
Researchers have characterized the cost of achieving valid per-class coverage in recognition systems when distribution shift occurs between training and testing data. They found that while split conformal prediction mai…
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New research advances conformal prediction for uncertainty quantification · 8 sources tracked
Researchers have developed new theoretical frameworks and computational methods to enhance conformal prediction, a technique for quantifying uncertainty in machine learning models. One paper proposes an optimal data spl…
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New research questions conformal prediction metrics and proposes tail-specific guarantees
Two new research papers explore advancements and critical evaluations within conformal prediction. The first paper introduces a method for constructing prediction intervals with specific guarantees for both upper and lo…
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AI agents' credential exfiltration detected via activation probes
Researchers have developed new methods to detect when AI agents might be exfiltrating sensitive credentials. One approach uses activation probes to identify credential access before the agent even outputs information. A…