Enhancement of photoacoustic imaging systems for biomedical applications by Sharma, Arunima

“…The results demonstrated that improvement in imaging depth in breast tissue by NIR-II waves is due to the increased MPE in this region. To further enhance PA images, deep learning (DL) method was suggested to improve the out-of-focus resolution of AR-PAM systems. …”
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Efficient rare event sampling with unsupervised normalizing flows by Asghar, Solomon, Pei, Qing-Xiang, Volpe, Giorgio, Ni, Ran

“…Classical computational methods to sample rare events remain prohibitively inefficient and are bottlenecks for enhanced samplers that require prior data. Here we introduce a physics-informed machine learning framework, normalizing Flow enhanced Rare Event Sampler (FlowRES), which uses unsupervised normalizing flow neural networks to enhance Monte Carlo sampling of rare events by generating high-quality non-local Monte Carlo proposals. …”
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Deep learning and computer chess (part 2) by Lee, Zachary Varella Zheyu

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PLATON: top-down R-tree packing with learned partition policy by Yang, Jingyi, Cong, Gao

“…We develop a learned partition policy based on Monte Carlo Tree Search and carefully make design choices for the MCTS exploration strategy and simulation strategy to improve algorithm convergence. …”
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Quantum advantage for differential equation analysis by Kiani, Bobak Toussi, De Palma, Giacomo, Englund, Dirk, Kaminsky, William, Marvian, Milad, Lloyd, Seth

“…However, there also exist obstacles to obtaining this potential speedup in useful problem instances. The essential obstacle for quantum differential equation solving is that outputting useful information may require difficult postprocessing, and the essential obstacle for quantum data processing and machine learning is that inputting the data is a difficult task just by itself. …”
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