Abstract: Imbalanced image classification faces critical challenges in balancing the quality and diversity of synthetic minority samples. This article proposes the improved estimation distribution ...
Morning Overview on MSN
AI uncovers 1,300+ weird anomalies in 30 years of Hubble data
Artificial intelligence has just turned one of astronomy’s most familiar workhorses into a discovery engine all over again.
New research suggests that the electrical complexity of the brain diminishes in early Alzheimer’s disease, potentially signaling a breakdown in the neural networks that support conscious awareness. By ...
AI is ultimately a story about selfhood—and the answer will not be found in the machine, but in what mindful awareness allows ...
Tesla Full Self-Driving leverages cameras, neural networks, and real-world testing to navigate traffic safely, advancing ...
Machine learning holds great promise for classifying and identifying fossils, and has recently been marshaled to identify trackmakers of dinosaur ...
The line between human and artificial intelligence is growing ever more blurry. Since 2021, AI has deciphered ancient texts ...
Evolving challenges and strategies in AI/ML model deployment and hardware optimization have a big impact on NPU architectures ...
A new technical paper titled “A Case for Hypergraphs to Model and Map SNNs on Neuromorphic Hardware” was published by ...
In a Nature Communications study, researchers from China have developed an error-aware probabilistic update (EaPU) method ...
It shows the schematic of the physics-informed neural network algorithm for pricing European options under the Heston model. The market price of risk is taken to be λ=0. Automatic differentiation is ...
TPUs are Google’s specialized ASICs built exclusively for accelerating tensor-heavy matrix multiplication used in deep learning models. TPUs use vast parallelism and matrix multiply units (MXUs) to ...
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