eLife

Reassessing prediction in the brain: Pre-onset neural encoding during natural listening does not reflect pre-activation

This study presents valuable findings by reanalyzing previously published MEG and ECoG datasets to challenge the predictive nature of pre-onset neural encoding effects. The evidence supporting the ...
Opinion

How do different data preprocessing techniques affect performance of machine learning models on prediction tasks?

Artificial intelligence (AI) and machine learning (ML) systems have become central to modern data-driven decision-making. They are now widely applied in fields as diverse as healthcare, finance, ...
EurekAlert!

A domain generalization method for EEG based on domain-invariant feature and data augmentation

(A) Overall structure of the model. MLP, multilayer perceptron. (B) Structure of the time encoder module. (C) Structure of the channel encoder module. BN, batch normalization. “Domain bias caused by ...
IEEE

Causal Meta-Learning Framework: A Co-Evolutionary Approach to Disentanglement and Generalization for Fault Diagnosis of Rotating Machinery

Abstract: The generalization of intelligent fault diagnosis models under unseen operating conditions remains a significant challenge due to the complex and variable environments of rotating machinery.
JD Supra

FDA Modernizes Draft Guidance on Statistical Methods to Support Clinical Trial Data

Consistent with the Food and Drug Administration’s (FDA) commitment to streamlining the prescription drug and biologics approval processes by adopting innovative approaches to clinical trial design, ...
eLife

Prior cocaine use disrupts identification of hidden states by single units and neural ensembles in orbitofrontal cortex

Rats with a history of cocaine use exhibited prolonged encoding of idiosyncratic task features in orbitofrontal cortex and a reduced ability to compress such features to identify underlying hidden ...
EurekAlert!

Pusan National University scientists develop robust “Huber mean” for geometric data

The newly developed Huber mean provides a more stable and reliable way to compute averages for data lying on curved geometric spaces, or Riemannian manifolds. By combining the strengths of ...
IEEE

Learning Intrinsic Invariance Within Intra-Class for Domain Generalization

Abstract: Deep learning methods often struggle with the domain shift problem, leading to poor generalization on out-of-domain (OOD) data. To address the problem, domain generalization (DG) has been ...
Reuters

OpenAI and others seek new path to smarter AI as current methods hit limitations

AI companies face delays and challenges with training new large language models Some researchers are focusing on more time for inference in new models Shift could impact AI arms race for resources ...
The Heritage Foundation

Beyond the Ballot: A Survey of Statistical Methods for Uncovering Election Anomalies

A variety of statistical tools can detect potential breaches in the integrity of elections. These techniques draw on tools from many fields, including pure mathematics, statistics, and machine ...
marktechpost

Understanding Memorization in Diffusion Models: A Statistical Physics Approach to Manifold-Supported Data

Generative diffusion models have revolutionized image and video generation, becoming the foundation of state-of-the-art generation software. While these models excel at handling complex ...