A novel machine learning model called Temporal Autoencoders for Causal Inference (TACI) accurately detects changing cause-and ...

A new computer model can more accurately assess how causal relationships in complex real-world systems vary over time.

This paper is based on the elementary remark that the extraction of gauge invariant results from a formally gauge invariant theory is ensured if one employs methods of solution that involve only gauge ...

They demonstrated that the interference patterns depended only on the net flux through the rings, confirming the gauge ...

Abstract: Adversarial attacks pose a huge challenge to the deployment of deep neural networks (DNNs) in security-sensitive applications. Adversarial defense methods are developed to resist adversarial ...

To tackle this problem, we propose Decoupling Domain Invariance and Variance with Tailored Prompts (PromptDIV) for OSDA to learn domain-invariant features for alignment. Specifically, we propose ...

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