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文集引用的一手文献。题名与书目信息保留原文,便于准确核查。
第 241–264 条,共 766 条来源
Efficient Test-Time Model Adaptation without Forgetting
Shuaicheng Niu; Jiaxiang Wu; Yifan Zhang; Yaofo Chen; Shijian Zheng; Peilin Zhao; Mingkui Tan打开原始来源 ↗
2022Efficiently Modeling Long Sequences with Structured State Spaces
Albert Gu; Karan Goel; Christopher Ré打开原始来源 ↗
2021Electrochemical Na Insertion and Solid Electrolyte Interphase for Hard‐Carbon Electrodes and Application to Na‐Ion Batteries
Shinichi Komaba; Wataru Murata; Toru Ishikawa; Naoaki Yabuuchi; Tomoaki Ozeki; Tetsuri Nakayama; Atsushi Ogata; Kazuma Gotoh; Kazuya Fujiwara打开原始来源 ↗
2011Eluding Secure Aggregation in Federated Learning via Model Inconsistency
Dario Pasquini; Danilo Francati; Giuseppe Ateniese打开原始来源 ↗
2022Emerging Properties in Self-Supervised Vision Transformers
Mathilde Caron; Hugo Touvron; Ishan Misra; Hervé Jégou; Julien Mairal; Piotr Bojanowski; Armand Joulin打开原始来源 ↗
2021End-to-end Optimized Image Compression
Johannes Ballé; Valero Laparra; Eero P. Simoncelli打开原始来源 ↗
2017Enhanced cation interaction in perovskites for efficient tandem solar cells with silicon
Esma Ugur; Ahmed Ali Said; Pia Dally; Shanshan Zhang; Christopher E. Petoukhoff; Diego Rosas-Villalva; et al.
2024-08-02来源定位: Abstract; interface and stability characterization
核查范围: 特定添加与器件实验,不将短测试等同30年寿命。
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Enhanced prime editing systems by manipulating cellular determinants of editing outcomes
Peter J. Chen; Jeffrey A. Hussmann; Jun Yan; Friederike Knipping; Purnima Ravisankar; Pin-Fang Chen; et al.
2021-10来源定位: Abstract; mismatch-repair and PEmax results
核查范围: 比较细胞修复环境对引导编辑结果的影响,不将某体系效率外推临床。
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Equivalent-accuracy accelerated neural-network training using analogue memory
Stefano Ambrogio; Pritish Narayanan; Hsinyu Tsai; Robert M. Shelby; Irem Boybat; Carmelo di Nolfo; Severin Sidler; Massimo Giordano; Martina Bodini; Nathan C. P. Farinha; Benjamin Killeen; Christina Cheng; Yassine Jaoudi; Geoffrey W. Burr打开原始来源 ↗
2018Error estimates for DeepOnets: A deep learning framework in infinite dimensions
Samuel Lanthaler; Siddhartha Mishra; George Em Karniadakis打开原始来源 ↗
2021Estimating the permanent loss of groundwater storage in the southern <scp>S</scp>an <scp>J</scp>oaquin <scp>V</scp>alley, <scp>C</scp>alifornia
R. G. Smith; R. Knight; J. Chen; J. A. Reeves; H. A. Zebker; T. Farr; Z. Liu打开原始来源 ↗
2017Eternal Sunshine of the Spotless Net: Selective Forgetting in Deep Networks
Aditya Golatkar; Alessandro Achille; Stefano Soatto打开原始来源 ↗
2020引用本来源的文章 (1)
Evaluating model calibration in classification
Juozas Vaicenavicius; David Widmann; Carl Andersson; Fredrik Lindsten; Jacob Roll; Thomas B. Schön打开原始来源 ↗
2019Evidence of a Phonon Hall Effect in the Kitaev Spin Liquid Candidate <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mrow><mml:mi>α</mml:mi><mml:mtext>−</mml:mtext><mml:msub><mml:mrow><mml:mi>RuCl</mml:mi></mml:mrow><mml:mrow><mml:mn>3</mml:mn></mml:mrow></mml:msub></mml:mrow></mml:math>
É. Lefrançois; G. Grissonnanche; J. Baglo; P. Lampen-Kelley; J.-Q. Yan; C. Balz; D. Mandrus; S. E. Nagler; S. Kim; Young-June Kim; N. Doiron-Leyraud; Louis Taillefer打开原始来源 ↗
2022Experimental demonstration of information-to-energy conversion and validation of the generalized Jarzynski equality
Shoichi Toyabe; Takahiro Sagawa; Masahito Ueda; Eiro Muneyuki; Masaki Sano打开原始来源 ↗
2010Experimental verification of Landauer’s principle linking information and thermodynamics
Antoine Bérut; Artak Arakelyan; Artyom Petrosyan; Sergio Ciliberto; Raoul Dillenschneider; Eric Lutz打开原始来源 ↗
2012Explaining and Harnessing Adversarial Examples
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2014-12-20来源定位: Abstract; 原文方法、理论和实验章节见作者原始论文链接
核查范围: 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。
查阅日期: 2026-10-21
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Explaining and Harnessing Adversarial Examples
Ian J. Goodfellow; Jonathon Shlens; Christian Szegedy打开原始来源 ↗
2014引用本来源的文章 (1)
Explaining Neural Scaling Laws
Yasaman Bahri; Ethan Dyer; Jared Kaplan; Jaehoon Lee; Utkarsh Sharma打开原始来源 ↗
2024Exploring Deep Neural Networks via Layer-Peeled Model: Minority Collapse in Imbalanced Training
Cong Fang; Hangfeng He; Qi Long; Weijie J. Su打开原始来源 ↗
2021Exploring Generalization in Deep Learning
Behnam Neyshabur; Srinadh Bhojanapalli; David McAllester; Nathan Srebro打开原始来源 ↗
2017Exploring Length Generalization in Large Language Models
Cem Anil; Yuhuai Wu; Anders Andreassen; Aitor Lewkowycz; Vedant Misra; Vinay Ramasesh; Ambrose Slone; Guy Gur-Ari; Ethan Dyer; Behnam Neyshabur打开原始来源 ↗
2022Exploring Simple Siamese Representation Learning
Xinlei Chen; Kaiming He打开原始来源 ↗
2020Extending Context Window of Large Language Models via Positional Interpolation
Shouyuan Chen; Sherman Wong; Liangjian Chen; Yuandong Tian打开原始来源 ↗
2023