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Physical modeling, including aerospace and complex fluid flow
Biological modeling, including bacterial dynamics and neuron potential
Epidemiology
Abstract
USC researchers introduce a novel method to solve partial differential equations (PDEs) using a multiwavelet-based neural operator learning scheme. By compressing the operator's kernel using...
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Big data analytics
Abstract
USC researchers have developed an optimization technique that finds the best data location scheme for PIM systems. This technique improves both performance and energy consumption. Experimental results demonstrate that this technique improves system performance by 9.8x and achieves a 2.3x energy reductions, compared to...
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Market Opportunity
There is a growing need for high-performance, low-latency, and energy-efficient hardware in autonomous systems, robotics, brain-machine interfaces, edge AI, and cyber-physical systems. Existing HLS tools often fail to efficiently exploit parallelism, optimize memory bandwidth, or generate domain-specific accelerator architectures...
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Drug discovery
Antibacterial resistance
Treatment of life-threatening and rare diseases
Abstract
USC researchers have developed a machine learning approach that can infer drug properties from known information about drug-target interactions. The technique is used to build a weighted Drug-Drug Similarity Network that can generate drug communities...
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Epilepsy treatment
Abstract
USC researchers propose a method to stabilize linear fractional-order systems using linear matrix inequalities. The approach addresses the challenge of stability in these systems and offers insights into mitigating epilepsy. The main contributions of this work include providing tractable conditions for the global asymptotic...
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