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arXiv 2023年

作者： Zheng, Kaizhong Yu, Shujian Chen, Badong National Key Laboratory of Human-Machine Hybrid Augmented Intelligence National Engineering Research Center for Visual Information and Applications Institute of Artificial Intelligence and Robotics Xi'an Jiaotong University Xi’an China Department of Computer Science Vrije Universiteit Amsterdam Amsterdam Netherlands Machine Learning Group UiT - Arctic University of Norway Tromsø Norway

There is a recent trend to leverage the power of graph neural networks (GNNs) for brain-network based psychiatric diagnosis, which, in turn, also motivates an urgent need for psychiatrists to fully understand the decision behavior of the used GNNs. However, most of the existing GNN explainers are either post-hoc in which another interpretive model needs to be created to explain a well-trained GNN, or do not consider the causal relationship between the extracted explanation and the decision, such that the explanation itself contains spurious correlations and suffers from weak faithfulness. In this work, we propose a granger causality-inspired graph neural network (CI-GNN), a built-in interpretable model that is able to identify the most influential subgraph (i.e., functional connectivity within brain regions) that is causally related to the decision (e.g., major depressive disorder patients or healthy controls), without the training of an auxillary interpretive network. CI-GNN learns disentangled subgraph-level representations α and β that encode, respectively, the causal and non-causal aspects of original graph under a graph variational autoencoder framework, regularized by a conditional mutual information (CMI) constraint. We theoretically justify the validity of the CMI regulation in capturing the causal relationship. We also empirically evaluate the performance of CI-GNN against three baseline GNNs and four state-of-the-art GNN explainers on synthetic data and three large-scale brain disease datasets. We observe that CI-GNN achieves the best performance in a wide range of metrics and provides more reliable and concise explanations which have clinical evidence. The source code and implementation details of CI-GNN are freely available at GitHub repository (https://***/ZKZ-Brain/CI-GNN/). Copyright © 2023, The Authors. All rights reserved.

关键词： Diagnosis

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General limit to thermodynamic annealing performance

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Physical Review E 2023年第5期108卷 L052105-L052105页

作者： Yutong Luo Yi-Zheng Zhen Xiangjing Liu Daniel Ebler Oscar Dahlsten Blackett Laboratory Imperial College London London SW7 2AZ United Kingdom Department of Physics Southern University of Science and Technology Shenzhen 518055 China Hefei National Research Center for Physical Sciences at the Microscale and School of Physical Sciences University of Science and Technology of China Hefei 230026 China Shanghai Research Center for Quantum Science and CAS Center for Excellence in Quantum Information and Quantum Physics University of Science and Technology of China Shanghai 201315 China Theory Laboratory Central Research Institute 2012 Labs Huawei Technology Company Limited Hong Kong Science Park Hong Kong SAR China Department of Computer Science The University of Hong Kong Pokfulam Road Hong Kong SAR China Department of Physics City University of Hong Kong Tat Chee Avenue Kowloon Hong Kong SAR China Shenzhen Institute for Quantum Science and Engineering and Department of Physics Southern University of Science and Technology Shenzhen 518055 China Institute of Nanoscience and Applications Southern University of Science and Technology Shenzhen 518055 China

Annealing has proven highly successful in finding minima in a cost landscape. Yet, depending on the landscape, systems often converge towards local minima rather than global ones. In this Letter, we analyze the conditions for which annealing is approximately successful in finite time. We connect annealing to stochastic thermodynamics to derive a general bound on the distance between the system state at the end of the annealing and the ground state of the landscape. This distance depends on the amount of state updates of the system and the accumulation of nonequilibrium energy, two protocol and energy landscape-dependent quantities which we show are in a trade-off relation. We describe how to bound the two quantities both analytically and physically. This offers a general approach to assess the performance of annealing from accessible parameters, both for simulated and physical implementations.

关键词： Nonequilibrium statistical mechanics Quantum thermodynamics

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Bound on annealing performance from stochastic thermodynamics, with application to simulated annealing

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Physical Review E 2023年第5期108卷 054119-054119页

作者： Yutong Luo Yi-Zheng Zhen Xiangjing Liu Daniel Ebler Oscar Dahlsten Blackett Laboratory Imperial College London London SW7 2AZ United Kingdom Department of Physics Southern University of Science and Technology Shenzhen 518055 China Hefei National Research Center for Physical Sciences at the Microscale and School of Physical Sciences University of Science and Technology of China Hefei 230026 China Shanghai Research Center for Quantum Science and CAS Center for Excellence in Quantum Information and Quantum Physics University of Science and Technology of China Shanghai 201315 China Theory Lab Central Research Institute 2012 Labs Huawei Technology Co. Ltd. Hong Kong Science Park Hong Kong SAR China Department of Computer Science The University of Hong Kong Pokfulam Road Hong Kong SAR China Department of Physics City University of Hong Kong Tat Chee Avenue Kowloon Hong Kong SAR China Shenzhen Institute for Quantum Science and Engineering and Department of Physics Southern University of Science and Technology Shenzhen 518055 China Institute of Nanoscience and Applications Southern University of Science and Technology Shenzhen 518055 China

Annealing is the process of gradually lowering the temperature of a system to guide it towards its lowest energy states. In an accompanying paper [Y. Luo et al., Phys. Rev. E 108, L052105 (2023)], we derived a general bound on annealing performance by connecting annealing with stochastic thermodynamics tools, including a speed limit on state transformation from entropy production. We here describe the derivation of the general bound in detail. In addition, we analyze the case of simulated annealing with Glauber dynamics in depth. We show how to bound the two case-specific quantities appearing in the bound, namely the activity, a measure of the number of microstate jumps, and the change in relative entropy between the state and the instantaneous thermal state, which is due to temperature variation. We exemplify the arguments by numerical simulations on the Sherrington-Kirkpatrick (SK) model of spin glasses.

关键词： Nonequilibrium statistical mechanics Quantum statistical mechanics

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Phase Correction of MR Spectroscopic Imaging Data Using Model-Based Signal Estimation and Extrapolation

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IEEE Transactions on Biomedical engineering 2025年 PP卷 PP页

作者： Jin, Wen Guo, Rong Li, Yudu Zhao, Yibo Li, Xin Zhu, Xiao-Hong Chen, Wei Liang, Zhi-Pei University of Illinois at Urbana-Champaign Beckman Institute for Advanced Science and Technology Department of Electrical and Computer Engineering Urbana IL United States University of Illinois at Urbana-Champaign Beckman Institute for Advanced Science and Technology Urbana IL United States Siemens Medical Solutions USA Inc. Malvern PA United States University of Illinois at Urbana-Champaign Beckman Institute for Advanced Science and Technology Department of Bioengineering National Center for Supercomputing Applications Urbana IL United States University of Minnesota Department of Radiology Center for Magnetic Resonance Research Minneapolis MN United States

Objective: To develop an effective method for phase correction of magnetic resonance spectroscopic imaging (MRSI) data. Methods: In many MRSI applications, it is desirable to generate absorption-mode spectra, which requires correction of phase errors in the measured MRSI data. Conventional phase correction methods are sensitive to measurement noise and baseline distortion, often resulting in distorted absorption-mode spectra from MRSI data with low-SNR and long acquisition dead time. This paper proposed a novel model-based method for improved phase correction of MRSI data. The proposed method determined the zeroth-order phase and acquisition dead time using a Lorentzian-based spectral model and performed signal extrapolation using a generalized series model. Absorption-mode spectra were then generated from the phase-corrected and extrapolated MRSI data. Results: The proposed method was evaluated using both simulated data and experimental data acquired from human subjects in multi-nuclei ( ³¹P, ²H, and ¹H) MRSI experiments. Simulation results demonstrated improved parameter estimation accuracy by the proposed method under various noise levels and dead times. The proposed method also consistently generated high-quality absorption-mode spectra with minimal spectral distortions from experimental data. The proposed method was compared with state-of-the-art methods (including the entropy method and LCModel method) and showed more robust phase correction performance with less spectral distortions. Conclusion: This paper introduced a novel method for phase correction of MRSI data. Results from simulated and in vivo data demonstrated that high-quality absorption-mode spectra could be obtained using the proposed method. Significance: This method will provide a useful tool for processing MRSI data. © 1964-2012 IEEE.

关键词： Absorption-mode spectrum generalized series model MRSI phase correction subspace model

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Strong nanophotonic quantum squeezing exceeding 3.5 dB in a foundry-compatible Kerr microresonator

arXiv

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arXiv 2024年

作者： Shen, Yichen Hsieh, Ping-Yen Sridhar, Sashank Kaushik Feldman, Samantha Chang, You-Chia Smith, Thomas A. Dutt, Avik Department of Mechanical Engineering Institute for Physical Science & Technology University of Maryland College ParkMD20742 United States Department of Photonics College of Electrical and Computer Engineering National Yang Ming Chiao Tung University Hsinchu30069 Taiwan Department of Mechanical Engineering and Materials Science Washington University St. LouisMO63130 United States Quantum Research and Applications Branch Naval Air Warfare Center Patuxent RiverMD20670 United States at Maryland College ParkMD20740 United States

Squeezed light, with its quantum noise reduction capabilities, has emerged as a powerful resource in quantum information processing and precision metrology. To reach noise reduction levels such that a quantum advantage is achieved, off-chip squeezers are typically used. The development of on-chip squeezed light sources, particularly in nanophotonic platforms, has been challenging. We report 3.7 ± 0.2 dB of directly detected nanophotonic quantum squeezing using foundry-fabricated silicon nitride (Si3N4) microrings with an inferred squeezing level of 10.7 dB on-chip. The squeezing level is robust across multiple devices and pump detunings, and is consistent with the overcoupling degree without noticeable degradation from excess classical noise. We also offer insights to mitigate thermally-induced excess noise, that typically degrades squeezing, by using small-radius rings with a larger free spectral range (450 GHz) and consequently lower parametric oscillation thresholds. Our results demonstrate that Si3N4 is a viable platform for strong quantum noise reduction in a CMOS-compatible, scalable architecture. Copyright © 2024, The Authors. All rights reserved.

关键词： Silicon nitride

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Efficient Online and Privacy-preserving Medical Pre-diagnosis Based on Growing Learning Vector Quantization

Efficient Online and Privacy-preserving Medical Pre-diagnosi...

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International Conference on Advanced Cloud and Big Data (CBD)

作者： Xiao Zheng Qiuyue Zhang Xuan Tang Xiujun Wang Chunlai Du School of Computer Science and Technology Anhui University of Technology Maanshan-Anhui China Institute of Artificial Intelligence Hefei Comprehensive National Science Center Hefei-Anhui China Anhui Engineering Research Center for Intelligent Applications and Security of Industrial Internet Maanshan-Anhui China School of Information Science and Technology North China University of Technology Beijing China

ISBN: (纸本)9798350309720

With more and more people turning to online medical pre-diagnosis systems, it becomes increasingly important to protect patient privacy and enhance the accuracy and efficiency of diagnosis. That is because the ever rapidly growing medical records not only contain a large amount of private information but are often highly unequally distributed (e.g., the number of cases and the rate of increase of covid-19 can be much higher than that of common diseases). However, existing methods are not capable of simultaneously boosting the intensity of privacy protection, and the accuracy and efficiency of diagnosis. In this paper, we propose an online medical pre-diagnosis scheme based on incremental learning vector quantization (called WL-OMPD) to achieve the two objectives at the same time. Specifically, within WL-OMPD, we design an efficient algorithm, Wasserstein-Learning Vector Quantization (W-LVQ), to smartly compress the original medical records into hypothetic samples. Then, we transmit these compressed data to the cloud instead of the original records to offer a more accurate pre-diagnosis. Extensive evaluations of real medical datasets show that the WL-OMPD scheme can improve the imbalance ratio of the data to a certain extent and then the intensity of privacy protection. These results also demonstrate that WL-OMPD substantially boost the accuracy of the classification model and increase diagnostic efficiency at a lower compression rate.

关键词： Privacy Data privacy Vector quantization Turning Explosions Data models Classification algorithms

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Building Knowledge-Grounded Dialogue Systems with Graph-Based Semantic Modeling

arXiv

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arXiv 2022年

作者： Yang, Yizhe Huang, Heyan Gao, Yang Li, Jiawei School of Computer Science and Technology Beijing Institute of Technology Beijing100081 China Southeast Academy of Information Technology Beijing Institute of Technology Fujian Putian351100 China Beijing Engineering Research Center of High Volume Language Information Processing and Cloud Computing Applications Beijing China

The knowledge-grounded dialogue task aims to generate responses that convey information from given knowledge documents. However, it is a challenge for the current sequence-based model to acquire knowledge from complex documents and integrate it to perform correct responses without the aid of an explicit semantic structure. To address these issues, we propose a novel graph structure, Grounded Graph (G2), that models the semantic structure of both dialogue and knowledge to facilitate knowledge selection and integration for knowledge-grounded dialogue generation. We also propose a Grounded Graph Aware Transformer (G2AT) model that fuses multi-forms knowledge (both sequential and graphic) to enhance knowledge-grounded response generation. Our experiments results show that our proposed model outperforms the previous state-of-the-art methods with more than 10% gains in response generation and nearly 20% improvement in factual consistency. Further, our model reveals good generalization ability and robustness. By incorporating semantic structures as prior knowledge in deep neural networks, our model provides an effective way to aid language generation. Copyright © 2022, The Authors. All rights reserved.

关键词： Deep neural networks

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Deep Hierarchical Attention Flow for Visual Commonsense Reasoning 1

引用

9th CCF International Conference on Natural Language Processing and Chinese Computing, NLPCC 2020

作者： Song, Yuansheng Jian, Ping School of Computer Science and Technology Beijing Institute of Technology Beijing China Beijing Engineering Research Center of High Volume Language Information Processing and Cloud Computing Applications Bejing China

ISBN: (数字)9783030604509

ISBN: (纸本)9783030604493

Visual Commonsense Reasoning (VCR) requires a thoroughly understanding general information connecting language and vision, as well as the background world knowledge. In this paper, we introduce a novel yet powerful deep hierarchical attention flow framework, which takes full advantage of text information in the query and candidate responses to perform reasoning over the image. Moreover, inspired by the success of machine reading comprehension, we also model the correlation among candidate responses to obtain better response representations. Extensive quantitative and qualitative experiments are conducted to evaluate the proposed model. Empirical results on the benchmark VCR1.0 show that the proposed model outperforms existing strong baselines, which demonstrates the effectiveness of our method. © 2020, Springer Nature Switzerland AG.

关键词： Visual languages

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Versatile spaceborne photonics with chalcogenide phase-change materials

arXiv

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arXiv 2023年

作者： Kim, Hyun Jung Julian, Matthew Williams, Calum Bombara, David Hu, Juejun Gu, Tian Aryana, Kiumars Sauti, Godfrey Humphreys, William NASA Langley Research Center HamptonVA United States Booz Allen Hamilton ArlingtonVA United States Department of Physics University of Cambridge CambridgeCB3 0HE United Kingdom John A. Paulson School of Engineering and Applied Sciences Harvard University CambridgeMA United States Department of Materials Science & Engineering Massachusetts Institute of Technology CambridgeMA United States Materials Research Laboratory Massachusetts Institute of Technology CambridgeMA United States

Recent growth in space systems has seen increasing capabilities packed into smaller and lighter Earth observation and deep space mission spacecraft. Phase-change materials (PCMs) are nonvolatile, reconfigurable, fast-switching, and have recently shown a high degree of space radiation tolerance, thereby making them an attractive materials platform for spaceborne photonics applications. They promise robust, lightweight, and energy-efficient reconfigurable optical systems whose functions can be dynamically defined on-demand and on orbit to deliver enhanced science or mission support in harsh environments on lean power budgets. This comment aims to discuss the recent advances in rapidly growing PCM research and its potential to transition from conventional terrestrial optoelectronics materials platforms to versatile spaceborne photonic materials platforms for current and next-generation space and science missions. Materials International Space Station Experiment-14 (MISSE-14) mission-flown PCMs outside of the International Space Station (ISS) and key results and nasa examples are highlighted to provide strong evidence of the applicability of spaceborne photonics. © 2023, CC BY.

关键词： Orbits

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Synthetic frequency dimension state coupling in modulated LNOI ring cavity devices

Synthetic frequency dimension state coupling in modulated LN...

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Conference on Lasers and Electro-Optics (CLEO)

作者： Armandas Balčytis Xuan Hiep Dinh Tomoki Ozawa Yasutomo Ota Toshihiko Baba Satoshi Iwamoto Arnan Mitchell Thach G. Nguyen Integrated Photonics and Applications Centre RMIT University Melbourne VIC Australia Advanced Institute for Materials Research Tohoku University Sendai Japan Department of Applied Physics and Physico-Informatics Keio University Yokohama Japan Department of Electrical and Computer Engineering Yokohama National University Hodogaya-ku Yokohama Japan Research Center for Advanced Science and Technology The University of Tokyo Meguro-ku Tokyo Japan

We created a modulator-equipped thin-film lithium niobate integrated ring resonator simulating a synthetic frequency dimension tight-binding model. It produces frequency states spaced over a 600 GHz bandwidth. Reconfi... 详细信息

ISBN: (纸本)9781957171258

关键词： Electron beam lithography Frequency combs Frequency modulation Lithium niobate Ring resonators Waveguide modulators

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