参考来源

第 505–528 条，共 766 条来源

505. Oracle-Guided Component-Based Program Synthesis

     Susmit Jha; Sumit Gulwani; Sanjit A. Seshia; Ashish Tiwari
     2010
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     • Programs from Counterexamples: Synthesis, Specifications, and Oracle Limits

506. Orca: A Distributed Serving System for Transformer-Based Generative Models

     Gyeong-In Yu; Joo Seong Jeong; Geon-Woo Kim; Soojeong Kim; Byung-Gon Chun
     2022
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     • Serving Language Models Within a Memory Budget: Attention, Paging, and Scheduling

507. Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer

     Noam Shazeer; Azalia Mirhoseini; Krzysztof Maziarz; Andy Davis; Quoc Le; Geoffrey Hinton; Jeff Dean
     2017
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     • Sparse Experts Under Capacity and Routing Constraints

508. Overcoming catastrophic forgetting in neural networks

     James Kirkpatrick; Razvan Pascanu; Neil Rabinowitz; Joel Veness; Guillaume Desjardins; Andrei A. Rusu; Kieran Milan; John Quan; Tiago Ramalho; Agnieszka Grabska-Barwinska; Demis Hassabis; Claudia Clopath; Dharshan Kumaran; Raia Hadsell
     2017
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     • What a Continual Learner Remembers: Replay, Constraints, and the Accounting of Forgetting

509. P2-type Nax[Fe1/2Mn1/2]O2 made from earth-abundant elements for rechargeable Na batteries

     Naoaki Yabuuchi; Masataka Kajiyama; Junichi Iwatate; Heisuke Nishikawa; Shuji Hitomi; Ryoichi Okuyama; Ryo Usui; Yasuhiro Yamada; Shinichi Komaba
     2012
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     • Abundance Is Not Performance: Sodium-Ion Batteries from Electrode Metrics to Usable Packs

510. PAC-Bayesian Generalisation Error Bounds for Gaussian Process Classification

     Matthias Seeger
     2002
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     • Who Chose the Prior? PAC-Bayes Certificates, Data Dependence, and the Cost of Selection

511. Pac-Bayesian Supervised Classification: The Thermodynamics of Statistical Learning

     Olivier Catoni
     2007
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     • Who Chose the Prior? PAC-Bayes Certificates, Data Dependence, and the Cost of Selection

512. Parallel Declines in Pollinators and Insect-Pollinated Plants in Britain and the Netherlands

     J. C. Biesmeijer; S. P. M. Roberts; M. Reemer; R. Ohlemüller; M. Edwards; T. Peeters; et al.
     2006-07-21

     来源定位: Abstract; regional distribution comparisons

     核查范围: 地区共同衰退研究，不据相关性确定唯一原因。

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     • 传粉网络的功能韧性：物种多样性、共同失效与农业产出的证据

513. Parallel Physics-Informed Neural Networks via Domain Decomposition

     Khemraj Shukla; Ameya D. Jagtap; George Em Karniadakis
     2021
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     • Physics-Informed Learning Has a Scale: Residual Weighting, Units, and Error

514. Parameter-efficient Multi-task Fine-tuning for Transformers via Shared Hypernetworks

     Rabeeh Karimi Mahabadi; Sebastian Ruder; Mostafa Dehghani; James Henderson
     2021
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     • Weights as Conditional Outputs: Hypernetworks, Modulation, and the Limits of Parameter Sharing

515. Passive radiative cooling below ambient air temperature under direct sunlight

     Aaswath P. Raman; Marc Abou Anoma; Linxiao Zhu; Eden Rephaeli; Shanhui Fan
     2014
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     • Cooling beneath the Sky: Spectral Selectivity, Atmospheric Windows and System Boundaries

516. Path ORAM: An Extremely Simple Oblivious RAM Protocol

     Emil Stefanov; Marten van Dijk; Elaine Shi; T-H. Hubert Chan; Christopher Fletcher; Ling Ren; Xiangyao Yu; Srinivas Devadas
     2014
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     • Hiding the Address: Oblivious RAM, Leakage, and the Cost of Access Privacy

517. Paxos Made Simple

     Leslie Lamport
     2001
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     • Consensus Beyond the Happy Path: Safety, Progress, and the Cost of Quorums

518. Perceiver: General Perception with Iterative Attention

     Jaegle et al.
     2021-03-04

     来源定位: v2 abstract; latent bottleneck architecture

     核查范围: An asymmetric cross-attention bottleneck processes high-dimensional inputs and decouples input size from latent self-attention size.

     查阅日期: 2026-10-15

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     • 多模态表征的可迁移性：对比目标、信息瓶颈与跨分布失效

519. Perovskite/silicon tandem solar cells with bilayer interface passivation

     Jiang Liu; Yongcai He; Lei Ding; Hua Zhang; Qiaoyan Li; Lingbo Jia; et al.
     2024-09-05

     来源定位: Abstract; Fig. 4

     核查范围: 双层钝化与器件效率/稳定性；认证面积与工况需保留。

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     • 叠层太阳能电池的真正增益：效率、光谱失配与服役能量

520. Phase Diagram and Superconducting Dome of Infinite-Layer <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mrow><mml:msub><mml:mrow><mml:mi>Nd</mml:mi></mml:mrow><mml:mrow><mml:mn>1</mml:mn><mml:mo>−</mml:mo><mml:mi>x</mml:mi></mml:mrow></mml:msub><mml:msub><mml:mrow><mml:mi>Sr</mml:mi></mml:mrow><mml:mrow><mml:mi>x</mml:mi></mml:mrow></mml:msub><mml:msub><mml:mrow><mml:mi>NiO</mml:mi></mml:mrow><mml:mrow><mml:mn>2</mml:mn></mml:mrow></mml:msub></mml:mrow></mml:math> Thin Films

     Shengwei Zeng; Chi Sin Tang; Xinmao Yin; Changjian Li; Mengsha Li; Zhen Huang; Junxiong Hu; Wei Liu; Ganesh Ji Omar; Hariom Jani; Zhi Shiuh Lim; Kun Han; Dongyang Wan; Ping Yang; Stephen John Pennycook; Andrew T. S. Wee; Ariando Ariando
     2020
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     • A Superconducting Signature Is a Chain of Evidence: Nickelates, Interfaces and Competing Explanations

521. Phase Separation by Low Complexity Domains Promotes Stress Granule Assembly and Drives Pathological Fibrillization

     Amandine Molliex; Jamshid Temirov; Jihun Lee; Maura Coughlin; Anderson P. Kanagaraj; Hong Joo Kim; Tanja Mittag; J. Paul Taylor
     2015
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     • When a Droplet Is a Mechanism: Phase Separation, Kinetics and Causal Tests in Cells

522. PhaseNet: a deep-neural-network-based seismic arrival-time picking method

     Zhu and Beroza
     2018-10-13

     来源定位: Three-component waveform segmentation; P/S/noise and Northern California training; journal issue 2019.

     查阅日期: 2026-10-22

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     • 从波形检测到地震目录：学习拾取、关联定位与完备性的联合分析

523. Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding

     Chitwan Saharia; William Chan; Saurabh Saxena; Lala Li; Jay Whang; Emily Denton; Seyed Kamyar Seyed Ghasemipour; Burcu Karagol Ayan; S. Sara Mahdavi; Rapha Gontijo Lopes; Tim Salimans; Jonathan Ho; David J Fleet; Mohammad Norouzi
     2022
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     • Guidance Changes the Target: Conditional Diffusion Between Fidelity and Concentration

524. Phylogenetic ctDNA analysis depicts early-stage lung cancer evolution

     The TRACERx consortium; Christopher Abbosh; The PEACE consortium; Nicolai J. Birkbak; Gareth A. Wilson; Mariam Jamal-Hanjani; Tudor Constantin; Raheleh Salari; John Le Quesne; David A. Moore; Selvaraju Veeriah; Rachel Rosenthal; Teresa Marafioti; Eser Kirkizlar; Thomas B. K. Watkins; Nicholas McGranahan; Sophia Ward; Luke Martinson; Joan Riley; Francesco Fraioli; Maise Al Bakir; Eva Grönroos; Francisco Zambrana; Raymondo Endozo; Wenya Linda Bi; Fiona M. Fennessy; Nicole Sponer; Diana Johnson; Joanne Laycock; Seema Shafi; Justyna Czyzewska-Khan; Andrew Rowan; Tim Chambers; Nik Matthews; Samra Turajlic; Crispin Hiley; Siow Ming Lee; Martin D. Forster; Tanya Ahmad; Mary Falzon; Elaine Borg; David Lawrence; Martin Hayward; Shyam Kolvekar; Nikolaos Panagiotopoulos; Sam M. Janes; Ricky Thakrar; Asia Ahmed; Fiona Blackhall; Yvonne Summers; Dina Hafez; Ashwini Naik; Apratim Ganguly; Stephanie Kareht; Rajesh Shah; Leena Joseph; Anne Marie Quinn; Phil A. Crosbie; Babu Naidu; Gary Middleton; Gerald Langman; Simon Trotter; Marianne Nicolson; Hardy Remmen; Keith Kerr; Mahendran Chetty; Lesley Gomersall; Dean A. Fennell; Apostolos Nakas; Sridhar Rathinam; Girija Anand; Sajid Khan; Peter Russell; Veni Ezhil; Babikir Ismail; Melanie Irvin-Sellers; Vineet Prakash; Jason F. Lester; Malgorzata Kornaszewska; Richard Attanoos; Haydn Adams; Helen Davies; Dahmane Oukrif; Ayse U. Akarca; John A. Hartley; Helen L. Lowe; Sara Lock; Natasha Iles; Harriet Bell; Yenting Ngai; Greg Elgar; Zoltan Szallasi; Roland F. Schwarz; Javier Herrero; Aengus Stewart; Sergio A. Quezada; Karl S. Peggs; Peter Van Loo; Caroline Dive; C. Jimmy Lin; Matthew Rabinowitz; Hugo J. W. L. Aerts; Allan Hackshaw; Jacqui A. Shaw; Bernhard G. Zimmermann; Charles Swanton
     2017
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     • The Tumor Is Not a Sample: Spatial Evolution, Detection Limits and Longitudinal Inference

525. Physics Informed Deep Learning (Part I): Data-driven Solutions of Nonlinear Partial Differential Equations

     , ,
     2017-11-28

     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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     • 神经算子与偏微分方程：函数映射、频谱截断和物理误差

526. Physics Informed Deep Learning (Part I): Data-driven Solutions of Nonlinear Partial Differential Equations

     Maziar Raissi; Paris Perdikaris; George Em Karniadakis
     2017
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     • Physics-Informed Learning Has a Scale: Residual Weighting, Units, and Error

527. Pivot Tracing: Dynamic Causal Monitoring for Distributed Systems

     Jonathan Mace; Ryan Roelke; Rodrigo Fonseca
     2015
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     • Seeing a Distributed Execution: Sampling, Context, and the Limits of Trace Evidence

528. pLDDT: Understanding local confidence

     EMBL-EBI Training
     

     来源定位: Official AlphaFold training; local confidence interpretation

     核查范围: pLDDT is a per-residue local-confidence measure on a 0-100 scale, not a probability of biological function. Values above 90 indicate very high local confidence; above 70 generally supports backbone accuracy.

     查阅日期: 2026-10-15

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     • 蛋白质结构预测的证据层级：AlphaFold、置信度与实验边界