End-to-End Mesh Optimization of a Hybrid Deep Learning Black-Box PDE Solver

Kavli Affiliate: Yi Zhou | First 5 Authors: Shaocong Ma, James Diffenderfer, Bhavya Kailkhura, Yi Zhou, | Summary: Deep learning has been widely applied to solve partial differential equations (PDEs) in computational fluid dynamics. Recent research proposed a PDE correction framework that leverages deep learning to correct the solution obtained by a PDE solver on […]


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Dissecting Quantum Many-body Chaos in the Krylov Space

Kavli Affiliate: Huajia Wang | First 5 Authors: Liangyu Chen, Baoyuan Mu, Huajia Wang, Pengfei Zhang, | Summary: The growth of simple operators is essential for the emergence of chaotic dynamics and quantum thermalization. Recent studies have proposed different measures, including the out-of-time-order correlator and Krylov complexity. It is established that the out-of-time-order correlator serves […]


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Sensitivity analysis for publication bias in meta-analysis of sparse data based on exact likelihood

Kavli Affiliate: Yi Zhou | First 5 Authors: Taojun Hu, Yi Zhou, Sattoshi Hattori, , | Summary: Meta-analysis is a powerful tool to synthesize findings from multiple studies. The normal-normal random-effects model is widely used accounting for between-study heterogeneity. However, meta-analysis of sparse data, which may arise when the event rate is low for binary […]


Continue.. Sensitivity analysis for publication bias in meta-analysis of sparse data based on exact likelihood

Sensitivity analysis for publication bias in meta-analysis of sparse data based on exact likelihood

Kavli Affiliate: Yi Zhou | First 5 Authors: Taojun Hu, Yi Zhou, Satoshi Hattori, , | Summary: Meta-analysis is a powerful tool to synthesize findings from multiple studies. The normal-normal random-effects model is widely used to account for between-study heterogeneity. However, meta-analysis of sparse data, which may arise when the event rate is low for […]


Continue.. Sensitivity analysis for publication bias in meta-analysis of sparse data based on exact likelihood

Correlation decoupling of Casimir interaction in an electrolyte driven by external electric fields

Kavli Affiliate: Rudolf Podgornik | First 5 Authors: Guangle Du, David S. Dean, Bing Miao, Rudolf Podgornik, | Summary: It has been established for a long time that the long range van der Waals or thermal Casimir interaction between two semi-infinite dielectrics separated by a distance $H$ is screened by an intervening electrolyte. Here we […]


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Magneto-Induced Topological Phase Transition in Inverted InAs/GaSb Bilayers

Kavli Affiliate: Long Zhang | First 5 Authors: Zhongdong Han, Tingxin Li, Long Zhang, Rui-Rui Du, | Summary: We report a magneto-induced topological phase transition in inverted InAs/GaSb bilayers from a quantum spin Hall insulator to a normal insulator. We utilize a dual-gated Corbino device in which the degree of band inversion, or equivalently the […]


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Structural, magnetic and magnetocaloric properties of triangular-lattice transition-metal phosphates

Kavli Affiliate: Gang Su | First 5 Authors: Chuandi Zhang, Junsen Xiang, Quanliang Zhu, Longfei Wu, Shanfeng Zhang | Summary: The recent discovery of the spin supersolid candidate Na$_2$BaCo(PO$_4$)$_2$ stimulates numerous research interest on the triangular-lattice transition-metal phosphates. Here we report a comprehensive study on the structural, magnetic and magnetocaloric properties of polycrystalline Na$_2$$A$$T$(PO$_4$)$_2$ ($A$ […]


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Convergence Guarantees for RMSProp and Adam in Generalized-smooth Non-convex Optimization with Affine Noise Variance

Kavli Affiliate: Yi Zhou | First 5 Authors: Qi Zhang, Yi Zhou, Shaofeng Zou, , | Summary: This paper provides the first tight convergence analyses for RMSProp and Adam in non-convex optimization under the most relaxed assumptions of coordinate-wise generalized smoothness and affine noise variance. We first analyze RMSProp, which is a special case of […]


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Large-Scale Non-convex Stochastic Constrained Distributionally Robust Optimization

Kavli Affiliate: Yi Zhou | First 5 Authors: Qi Zhang, Yi Zhou, Ashley Prater-Bennette, Lixin Shen, Shaofeng Zou | Summary: Distributionally robust optimization (DRO) is a powerful framework for training robust models against data distribution shifts. This paper focuses on constrained DRO, which has an explicit characterization of the robustness level. Existing studies on constrained […]


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Facilitating Reinforcement Learning for Process Control Using Transfer Learning: Perspectives

Kavli Affiliate: Biao Huang | First 5 Authors: Runze Lin, Junghui Chen, Lei Xie, Hongye Su, Biao Huang | Summary: This paper provides insights into deep reinforcement learning (DRL) for process control from the perspective of transfer learning. We analyze the challenges of applying DRL in the field of process industries and the necessity of […]


Continue.. Facilitating Reinforcement Learning for Process Control Using Transfer Learning: Perspectives