Tag: causal machine learning
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Integrating Graph Embeddings in Event Sequence Models
Boost event sequence model accuracy by integrating graph-based embeddings for improved fraud detection and recommendations in digital platforms.
U-Cast: Efficient AI Weather Forecasting with U-Net Model
Discover U-Cast, an efficient AI weather forecaster using U-Net that cuts training time and boosts accuracy in probabilistic forecasts.
Noise-Aware Learning to Reduce Hallucinations in ALLMs
Discover how Noise-Aware In-Context Learning mitigates hallucinations in auditory large language models, improving accuracy without costly fine-tuning.
Regime-Conditional Retrieval for Improved Two-Hop QA Accuracy
Discover how regime-conditional retrieval and RegimeRouter boost two-hop QA accuracy with transferable routing across multiple datasets.
Measuring Bias Amplification in Multi-Agent Systems
Explore how multi-agent systems can amplify bias, revealing key risks and ethical challenges in complex AI workflows and system architectures.