Research library / Reference sources
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Reference sources

Primary references used in the research collection. Titles and bibliographic details retain their original language.

References 721–744 of 766

  1. Transformers are SSMs: Generalized Models and Efficient Algorithms Through Structured State Space Duality

    ,
    2024-05-31

    Source location: Abstract; 原文方法、理论和实验章节见作者原始论文链接

    Source scope: 一手论文;原文研究归属原作者。本文的推导示例与建议实验方案另行标注,不冒充原论文或本站实测。

    Inspected on: 2026-10-21

    Open original source ↗
    Referenced in (1)
  2. Transformers are SSMs: Generalized Models and Efficient Algorithms Through Structured State Space Duality

    Tri Dao; Albert Gu
    2024
    Open original source ↗
    Referenced in (1)
  3. Transformers learn in-context by gradient descent

    Johannes von Oswald; Eyvind Niklasson; Ettore Randazzo; João Sacramento; Alexander Mordvintsev; Andrey Zhmoginov; Max Vladymyrov
    2022
    Open original source ↗
    Referenced in (1)
  4. Transposon-encoded CRISPR–Cas systems direct RNA-guided DNA integration

    Sanne E. Klompe; Phuc L. H. Vo; Tyler S. Halpin-Healy; Samuel H. Sternberg
    2019-06-12

    Source location: Abstract; integration-site distribution

    Source scope: 另一类RNA引导整合系统;整合位置与完整性需单独评价。

    Open original source ↗
    Referenced in (1)
  5. Triptycene Induced Enhancement of Membrane Gas Selectivity for Microporous Tröger's Base Polymers

    Mariolino Carta; Matthew Croad; Richard Malpass‐Evans; Johannes C. Jansen; Paola Bernardo; Gabriele Clarizia; Karel Friess; Marek Lanč; Neil B. McKeown
    2014
    Open original source ↗
    Referenced in (1)
  6. Tutorial: Introduction to Datalog

    Souffle project
    2026
    Open original source ↗
    Referenced in (1)
  7. Ultrabroadband and band-selective thermal meta-emitters by machine learning

    Xiao et al.
    2025-07-02

    Source location: Machine-learning-guided three-dimensional photonic material design; optical and fabrication validation.

    Inspected on: 2026-10-22

    Open original source ↗
    Referenced in (1)
  8. Ultralow thermal conductivity and high thermoelectric figure of merit in SnSe crystals

    Li-Dong Zhao; Shih-Han Lo; Yongsheng Zhang; Hui Sun; Gangjian Tan; Ctirad Uher; C. Wolverton; Vinayak P. Dravid; Mercouri G. Kanatzidis
    2014
    Open original source ↗
    Referenced in (1)
  9. Uncertainties in Parameters Estimated with Neural Networks: Application to Strong Gravitational Lensing

    Perreault Levasseur, Hezaveh and Wechsler
    2017-08-29

    Source location: Variational uncertainty, coverage calibration and assumed lens family.

    Inspected on: 2026-10-22

    Open original source ↗
    Referenced in (1)
  10. Understanding and mitigating gradient pathologies in physics-informed neural networks

    Sifan Wang; Yujun Teng; Paris Perdikaris
    2020
    Open original source ↗
    Referenced in (1)
  11. Understanding Contrastive Representation Learning through Alignment and Uniformity on the Hypersphere

    Tongzhou Wang; Phillip Isola
    2020
    Open original source ↗
    Referenced in (1)
  12. Understanding Gradient Clipping in Private SGD: A Geometric Perspective

    Xiangyi Chen; Zhiwei Steven Wu; Mingyi Hong
    2020
    Open original source ↗
    Referenced in (1)
  13. Uniform Resource Identifier (URI): Generic Syntax (RFC 3986)

    Tim Berners-Lee; Roy T. Fielding; Larry Masinter
    2005
    Open original source ↗
    Referenced in (1)
  14. URL Standard

    WHATWG
    2026
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    Referenced in (1)
  15. Using EXPLAIN

    PostgreSQL Global Development Group
    2026
    Open original source ↗
    Referenced in (1)
  16. Variational Autoencoders and Nonlinear ICA: A Unifying Framework

    Ilyes Khemakhem; Diederik P. Kingma; Ricardo Pio Monti; Aapo Hyvärinen
    2019
    Open original source ↗
    Referenced in (1)
  17. Variational Image Compression with a Scale Hyperprior

    Johannes Ballé; David Minnen; Saurabh Singh; Sung Jin Hwang; Nick Johnston
    2018
    Open original source ↗
    Referenced in (1)
  18. Variational Mixture-of-Experts Autoencoders for Multi-Modal Deep Generative Models

    Yuge Shi; N. Siddharth; Brooks Paige; Philip H. S. Torr
    2019
    Open original source ↗
    Referenced in (1)
  19. Verifying Solutions to Semantics-Guided Synthesis Problems

    Charlie Murphy; Keith Johnson; Thomas Reps; Loris D'Antoni
    2025
    Open original source ↗
    Referenced in (1)
  20. Visualizing the Loss Landscape of Neural Nets

    Hao Li; Zheng Xu; Gavin Taylor; Christoph Studer; Tom Goldstein
    2018
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    Referenced in (1)
  21. Water harvesting from air with metal-organic frameworks powered by natural sunlight

    Hyunho Kim; Sungwoo Yang; Sameer R. Rao; Shankar Narayanan; Eugene A. Kapustin; Hiroyasu Furukawa; Ari S. Umans; Omar M. Yaghi; Evelyn N. Wang
    2017
    Open original source ↗
    Referenced in (1)
  22. Watermarks in Stream Processing Systems: Semantics and Comparative Analysis of Apache Flink and Google Cloud Dataflow

    Tyler Akidau; Edmon Begoli; Slava Chernyak; Fabian Hueske; Kathryn Knight; Kenneth Knowles; Daniel Mills; Dan Sotolongo
    2021
    Open original source ↗
    Referenced in (1)
  23. Weakly-Supervised Disentanglement Without Compromises

    Francesco Locatello; Ben Poole; Gunnar Rätsch; Bernhard Schölkopf; Olivier Bachem; Michael Tschannen
    2020
    Open original source ↗
    Referenced in (1)
  24. WeatherBench 2: A benchmark for the next generation of data-driven global weather models

    Rasp et al.
    2023-08-29

    Source location: Primary benchmark specification: initialization, regridding, reference analyses and multiple diagnostic metrics.

    Inspected on: 2026-10-22

    Open original source ↗
    Referenced in (2)