Probing reaction channels via reinforcement learning

Kavli Affiliate: David T. Limmer | First 5 Authors: Senwei Liang, Aditya N. Singh, Yuanran Zhu, David T. Limmer, Chao Yang | Summary: We propose a reinforcement learning based method to identify important configurations that connect reactant and product states along chemical reaction paths. By shooting multiple trajectories from these configurations, we can generate an […]


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Astrometric Calibration of the Beijing$-$Arizona Sky Survey

Kavli Affiliate: Linhua Jiang | First 5 Authors: Xiyan Peng, Zhaoxiang Qi, Tianmeng Zhang, Zhenyu Wu, Zhimin Zhou | Summary: We present the astrometric calibration of the Beijing-Arizona Sky Survey (BASS). The BASS astrometry was tied to the International Celestial Reference Frame via the emph{Gaia} Data Release 2 reference catalog. For effects that were stable […]


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Measuring Your ASTE Models in The Wild: A Diversified Multi-domain Dataset For Aspect Sentiment Triplet Extraction

Kavli Affiliate: Ting Xu | First 5 Authors: Ting Xu, Huiyun Yang, Zhen Wu, Jiaze Chen, Fei Zhao | Summary: Aspect Sentiment Triplet Extraction (ASTE) is widely used in various applications. However, existing ASTE datasets are limited in their ability to represent real-world scenarios, hindering the advancement of research in this area. In this paper, […]


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WELL: Applying Bug Detectors to Bug Localization via Weakly Supervised Learning

Kavli Affiliate: Zhuo Li | First 5 Authors: Zhuo Li, Huangzhao Zhang, Zhi Jin, Ge Li, | Summary: Bug localization, which is used to help programmers identify the location of bugs in source code, is an essential task in software development. Researchers have already made efforts to harness the powerful deep learning (DL) techniques to […]


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Bayesian target optimisation for high-precision holographic optogenetics

Kavli Affiliate: Liam Paninski | Authors: Marcus A Triplett, Marta Gajowa, Hillel Adesnik and Liam Paninski | Summary: Two-photon optogenetics has transformed our ability to probe the structure and function of neural circuits. However, achieving precise optogenetic control of neural ensemble activity has remained fundamentally constrained by the problem of off-target stimulation (OTS): the inadvertent […]


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Mouse models of SYNGAP1-related intellectual disability

Kavli Affiliate: Hey-Kyoung Lee, Richard Huganir | Authors: Yoichi Araki, Elizabeth E. Gerber, Kacey E. Rajkovich, Ingie Hong, Richard C. Johnson, Hey-Kyoung Lee, Alfredo Kirkwood and Richard L. Huganir | Summary: SYNGAP1 is a Ras-GTPase activating protein highly enriched at excitatory synapses in the brain. De novo loss-of-function mutations in SYNGAP1 are a major cause […]


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Contrasting synaptic roles of MDGA1 and MDGA2

Kavli Affiliate: Roger Nicoll | Authors: Michael A. Bemben, Matthew A. Sandoval, Aliza A. Le, Sehoon Won, Vivian N Chau, Julie C. Lauterborn, Salvatore Incontro, Kathy H. Li, Alma L. Burlingame, Katherine W. Roche, Christine M. Gall, Roger A. Nicoll and Javier Diaz-Alonso | Summary: Neurodevelopmental disorders are frequently linked to mutations in synaptic organizing […]


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GC-Flow: A Graph-Based Flow Network for Effective Clustering

Kavli Affiliate: Xiang Zhang | First 5 Authors: Tianchun Wang, Farzaneh Mirzazadeh, Xiang Zhang, Jie Chen | Summary: Graph convolutional networks (GCNs) are emph{discriminative models} that directly model the class posterior $p(y|mathbf{x})$ for semi-supervised classification of graph data. While being effective, as a representation learning approach, the node representations extracted from a GCN often miss […]


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Cluster Cosmology Without Cluster Finding

Kavli Affiliate: Risa H. Wechsler | First 5 Authors: Enia Xhakaj, Alexie Leauthaud, Johannes Lange, Elisabeth Krause, Andrew Hearin | Summary: We propose that observations of super-massive galaxies contain cosmological constraining power similar to conventional cluster cosmology, and we provide promising indications that the associated systematic errors are comparably easier to control. We consider a […]


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