Reference sources

References 241–264 of 766

241. Efficient Test-Time Model Adaptation without Forgetting

     Shuaicheng Niu; Jiaxiang Wu; Yifan Zhang; Yaofo Chen; Shijian Zheng; Peilin Zhao; Mingkui Tan
     2022
     Open original source ↗
     Referenced in (1)

     • When Inference Updates the Model: Test-Time Adaptation, Confidence, and State Drift

242. Efficiently Modeling Long Sequences with Structured State Spaces

     Albert Gu; Karan Goel; Christopher Ré
     2021
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     Referenced in (1)

     • What a Recurrent State Can Remember: Decay, Selectivity, and Sequence Memory

243. Electrochemical 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
     2011
     Open original source ↗
     Referenced in (1)

     • Abundance Is Not Performance: Sodium-Ion Batteries from Electrode Metrics to Usable Packs

244. Eluding Secure Aggregation in Federated Learning via Model Inconsistency

     Dario Pasquini; Danilo Francati; Giuseppe Ateniese
     2022
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     Referenced in (1)

     • A Sum without Its Summands: Secure Aggregation under Dropout and Collusion

245. Emerging Properties in Self-Supervised Vision Transformers

     Mathilde Caron; Hugo Touvron; Ishan Misra; Hervé Jégou; Julien Mairal; Piotr Bojanowski; Armand Joulin
     2021
     Open original source ↗
     Referenced in (1)

     • Learning from a Moving Teacher: Self-Distillation, Temporal Smoothing, and Collapse Boundaries

246. End-to-end Optimized Image Compression

     Johannes Ballé; Valero Laparra; Eero P. Simoncelli
     2017
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     Referenced in (1)

     • The Bits the Model Must Actually Send: Learned Image Compression and Entropy-Model Mismatch

247. Enhanced 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

     Source location: Abstract; interface and stability characterization

     Source scope: 特定添加与器件实验，不将短测试等同30年寿命。

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     Referenced in (1)

     • 叠层太阳能电池的真正增益：效率、光谱失配与服役能量

248. 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

     Source location: Abstract; mismatch-repair and PEmax results

     Source scope: 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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     Referenced in (1)

     • 引导编辑的精度账本：从序列改写到完整基因组结果的证据

249. 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
     2018
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     Referenced in (1)

     • When Multiplication Becomes Physics: Analog Neural Computing and the Energy of Everything Else

250. Error estimates for DeepOnets: A deep learning framework in infinite dimensions

     Samuel Lanthaler; Siddhartha Mishra; George Em Karniadakis
     2021
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     Referenced in (1)

     • Learning an Operator Across Grids: Resolution, Aliasing, and What Transfers

251. Estimating 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
     2017
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     Referenced in (1)

     • When Water Returns but Storage Does Not: Groundwater Depletion and Irreversible Compaction

252. Eternal Sunshine of the Spotless Net: Selective Forgetting in Deep Networks

     Aditya Golatkar; Alessandro Achille; Stefano Soatto
     2020
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     Referenced in (1)

     • What an Unlearning Test Can Actually Certify

253. Evaluating model calibration in classification

     Juozas Vaicenavicius; David Widmann; Carl Andersson; Fredrik Lindsten; Jacob Roll; Thomas B. Schön
     2019
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     Referenced in (1)

     • Calibrated Probabilities Are Not Yet Good Decisions

254. Evidence 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
     2022
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     Referenced in (1)

     • Beyond the Absence of Order: Identifying Quantum Spin Liquids amid Disorder and Imperfect Probes

255. Experimental demonstration of information-to-energy conversion and validation of the generalized Jarzynski equality

     Shoichi Toyabe; Takahiro Sagawa; Masahito Ueda; Eiro Muneyuki; Masaki Sano
     2010
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     Referenced in (1)

     • The Physical Price of Information: Erasure, Feedback and Finite-Time Thermodynamics

256. Experimental verification of Landauer’s principle linking information and thermodynamics

     Antoine Bérut; Artak Arakelyan; Artyom Petrosyan; Sergio Ciliberto; Raoul Dillenschneider; Eric Lutz
     2012
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     Referenced in (1)

     • The Physical Price of Information: Erasure, Feedback and Finite-Time Thermodynamics

257. Explaining and Harnessing Adversarial Examples

     , ,
     2014-12-20

     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)

     • 对抗鲁棒性的可检验边界：威胁模型、范数预算与攻击验收

258. Explaining and Harnessing Adversarial Examples

     Ian J. Goodfellow; Jonathon Shlens; Christian Szegedy
     2014
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     Referenced in (1)

     • Robustness Claims Need an Explicit Threat Model

259. Explaining Neural Scaling Laws

     Yasaman Bahri; Ethan Dyer; Jared Kaplan; Jaehoon Lee; Utkarsh Sharma
     2024
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     Referenced in (1)

     • Compute-Optimal Learning Depends on the Accounting

260. Exploring Deep Neural Networks via Layer-Peeled Model: Minority Collapse in Imbalanced Training

     Cong Fang; Hangfeng He; Qi Long; Weijie J. Su
     2021
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     Referenced in (1)

     • When Class Means Form a Simplex: Neural Collapse, Geometric Diagnostics, and Their Limits

261. Exploring Generalization in Deep Learning

     Behnam Neyshabur; Srinadh Bhojanapalli; David McAllester; Nathan Srebro
     2017
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     Referenced in (1)

     • The Same Predictor, a Sharper Minimum: Parameter Symmetry and the Meaning of Loss Geometry

262. Exploring 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
     2022
     Open original source ↗
     Referenced in (1)

     • Beyond the Training Window: Position, Distance, and Extrapolation in Transformers

263. Exploring Simple Siamese Representation Learning

     Xinlei Chen; Kaiming He
     2020
     Open original source ↗
     Referenced in (1)

     • Learning from a Moving Teacher: Self-Distillation, Temporal Smoothing, and Collapse Boundaries

264. Extending Context Window of Large Language Models via Positional Interpolation

     Shouyuan Chen; Sherman Wong; Liangjian Chen; Yuandong Tian
     2023
     Open original source ↗
     Referenced in (1)

     • Beyond the Training Window: Position, Distance, and Extrapolation in Transformers