arXiv Machine Learning June 15, 2026 By Dom CP Marticorena, Chris Wissmann, Zeyu Lu, Dennis L Barbour

Multidimensional Bayesian Active Machine Learning of Working Memory Task Performance

Read the original on arXiv Machine Learning →

arXiv:2510. 00375v2 Announce Type: replace Abstract: While adaptive experimental design has outgrown one-dimensional, staircase-based adaptations, most cognitive experiments still control a single factor and summarize performance with a scalar.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

arXiv Machine Learning

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Bayesian Distributional Models of Executive Functioning

arXiv:2510. 00387v4 Announce Type: replace Abstract: This study uses controlled simulations with known ground-truth parameters to evaluate how Distributional Latent Variable Models (DLVM) and Bayesian Distributional Active LEarning (DALE) perform in comparison to conventional Independent Maximum Likelihood Estimation (IMLE).

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arXiv AI

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Rendering-Aware Bayesian 3D Gaussian Splatting with Native Uncertainty and Adaptive Complexity Control

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arXiv AI

Aug 3

Identifying Informative Environments for Cognition Parameter Inference via Bayesian Experimental Design

arXiv:2607. 28894v1 Announce Type: new Abstract: Computational cognitive modeling seeks to infer latent cognitive mechanisms underlying observed behavior.

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arXiv AI

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ComMem: Complementary Memory Systems for Test-Time Adaptation of Vision-Language Models

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arXiv Machine Learning

Jul 9

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arXiv:2607. 07083v1 Announce Type: cross Abstract: Subsampling significantly reduces the number of measurements, thereby streamlining data processing and transfer overhead, and shortening acquisition time across diverse real-world applications.

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arXiv Machine Learning

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NeuroPareto: Calibrated Acquisition for Costly Many-Goal Search in Vast Parameter Spaces

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Bayesian Distributional Models of Executive Functioning

Rendering-Aware Bayesian 3D Gaussian Splatting with Native Uncertainty and Adaptive Complexity Control

Identifying Informative Environments for Cognition Parameter Inference via Bayesian Experimental Design

ComMem: Complementary Memory Systems for Test-Time Adaptation of Vision-Language Models

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NeuroPareto: Calibrated Acquisition for Costly Many-Goal Search in Vast Parameter Spaces