arXiv journal 2022.0213 interesting paper - 1

最新推荐文章于 2024-07-01 16:20:23 发布
最新推荐文章于 2024-07-01 16:20:23 发布
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A very nice historical review
Fifty years of Yang–Mills Theories: a phenomenological point of view
https://arxiv.org/pdf/hep-ph/0404215.pdf

abstract: On the occasion of the celebration of the first half-century of Yang–Mills theories, I am contributing a personal recollection of how the subject, in its early times, confronted physical reality, that is, its “phenomenology”. There is nothing original in this work, except, perhaps, my own points of view. But I hope that the older practitioners of the field will find here grounds for nostalgia, or good reasons to disagree with me. Younger addicts may learn that history does not resemble at all what is reflected in current textbooks: it was orders of magnitude more fascinating.

Deep Inelastic Scattering and Gauge/String Duality
https://arxiv.org/pdf/hep-th/0209211.pdf

Partons and Black Holes
https://arxiv.org/pdf/hep-ph/9410306.pdf

The Drell-Yan process
https://lib-extopc.kek.jp/preprints/PDF/1982/8208/8208150.pdf

Evidence of the gluon
https://lib-extopc.kek.jp/preprints/PDF/1981/8112/8112118.pdf

Experimental evidence on QCD
https://lib-extopc.kek.jp/preprints/PDF/1981/8104/8104332.pdf

Lepton pair production in hadronic collisions
https://lib-extopc.kek.jp/preprints/PDF/1981/8110/8110072.pdf

Deep inelastic structure functions
https://lib-extopc.kek.jp/preprints/PDF/1981/8102/8102075.pdf

Asymptotic freedom in deep inelastic process in leading-order and beyond
https://inspirehep.net/files/05b830f1b3bde5cdaeec793b022f11d5

QCD test and e+e- and pp colliders
https://lib-extopc.kek.jp/preprints/PDF/1988/8806/8806268.pdf

Invariant Theoretical Interpretation of Interaction
https://journals.aps.org/pr/pdf/10.1103/PhysRev.101.1597

Thermodynamic Stability Implies Causality
https://journals.aps.org/prl/pdf/10.1103/PhysRevLett.128.010606

https://inspirehep.net/files/bc886fef653f85f063743fb8569153d6

Relational inductive biases, deep learning, and graph networks（关系归纳偏差、深度学习和图形网络）
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目标检测经典论文——YOLOv3论文翻译：YOLOv3: An Incremental Improvement（YOLOv3：增量式的改进）
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YOLOv3: An Incremental Improvement YOLOv3：增量式的改进 Joseph Redmon Ali Farhadi University of Washington Abstract We present some updates to YOLO! We made a bunch of little design changes to make it better. We also trained this new networ...
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arXiv journal 2022.0213 interesting paper - DIS
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A paper of checking on how much difference is in between a functional-form parametrisation and neural network parametrisation. Function Approximation for High-Energy Physics: Comparing Machine Learning and Interpolation Methods https://arxiv.org/pdf/2111.1
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The philosophical basis of algorithmic recourse*
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