Fetching the paper…
Reading the bibliography…
Measurements from the Large Hadron Collider (LHC) and the Relativistic Heavy Ion Collider (RHIC) can be used to study the properties of quark-gluon plasma.
1912
Earlier work this paper cites.
H. Grad, On the kinetic theory of rarefied gases, Commun. Pure Appl. Math 2
1949
Earlier work this paper cites.
F. Cooper and G. Frye, Comment on the single particle distribution in the hydrodynamic and statistical thermodynamic models of multiparticle production, Phys. Rev. D 10
1974
Earlier work this paper cites.
F. Cooper, G. Frye, and E. Schonberg, Landau’s hydrodynamic model of particle production and electron positron annihilation into hadrons, Phys. Rev. D11
1975
Earlier work this paper cites.
J. Sacks, W. J. Welch, T. J. Mitchell, and H. P. Wynn, Design and Analysis of Computer Experiments, Statistical Science 4
1989
Earlier work this paper cites.
S. Chapman, T. G. Cowling, and D. Burnett, The mathematical theory of non-uniform gases: an account of the kinetic theory of viscosity, thermal conduction and diffusion in gases (Cambridge university press, 1990)
1990
Earlier work this paper cites.
I. M. Sobol’, On sensitivity estimation for nonlinear mathematical models, Matematicheskoe modelirovanie 2
1990
Earlier work this paper cites.
S. IM, Sensitivity estimates for nonlinear mathematical models, Math. Model. Comput. Exp 1
1993
Earlier work this paper cites.
M. D. Morris and T. J. Mitchell, Exploratory designs for computational experiments, Journal of Statistical Planning and Inference 43
1995
Earlier work this paper cites.
S. Bass and A. Dumitru, Dynamics of hot bulk QCD matter: From the quark gluon plasma to hadronic freezeout, Phys. Rev. C 61
2000
Earlier work this paper cites.
M. C. Kennedy and A. O’Hagan, Predicting the output from a complex computer code when fast approximations are available, Biometrika 87
2000
Earlier work this paper cites.
A. Kurganov and E. Tadmor, New High-Resolution Central Schemes for Nonlinear Conservation Laws and Convection-Diffusion Equations, Journal of Computational Physics 160
2000
Earlier work this paper cites.
M. C. Kennedy and A. O’Hagan, Bayesian calibration of computer models, Journal of the Royal Statistical Society: Series B (Statistical Methodology) 63
2001
Earlier work this paper cites.
J. Friedman, T. Hastie, and R. Tibshirani, The Elements of Statistical Learning (Springer Series in Statistics, 2001)
2001
Earlier work this paper cites.
T. J. Santner, B. J. Williams, W. I. Notz, and B. J. Williams, The Design and Analysis of Computer Experiments (Springer, 2003)
2003
Earlier work this paper cites.
C. E. Rasmussen, Gaussian processes in machine learning, in Advanced Lectures on Machine Learning: ML Summer Schools 2003, Canberra, Australia, February 2 - 14, 2003, Tübingen, Germany, August 4 - 16, 2003, Revised Lectures , edited by O. Bousquet, U. von Luxburg, and G. Rätsch (Springer Berlin Heidelberg, Berlin, Heidelberg, 2004) pp. 63–71
2004
Earlier work this paper cites.
M. Gyulassy and L. McLerran, New forms of QCD matter discovered at RHIC, Nucl. Phys. A 750
2005
Earlier work this paper cites.
K. Yagi, T. Hatsuda, and Y. Miake, Quark-Gluon Plasma: From Big Bang to Little Bang, Cambridge Monogr. Part. Phys. Nucl. Phys. Cosmol. 23
2005
Earlier work this paper cites.
J. Jacques, C. Lavergne, and N. Devictor, Sensitivity analysis in presence of model uncertainty and correlated inputs, Reliability Engineering & System Safety 91
2006
Earlier work this paper cites.
C. Nonaka and S. A. Bass, Space-time evolution of bulk QCD matter, Phys. Rev. C75
2007
Earlier work this paper cites.
W. Dai, Q. Yang, G.-R. Xue, and Y. Yu, Boosting for transfer learning, in Proceedings of the 24th International Conference on Machine Learning , ICML ’07 (Association for Computing Machinery, New York, NY, USA, 2007) p. 193–200
2007
Earlier work this paper cites.
R. Trotta, Bayes in the sky: Bayesian inference and model selection in cosmology, Contemporary Physics 49
2008
Earlier work this paper cites.
G. Peters, Markov Chain Monte Carlo: stochastic simulation for bayesian inference (2nd ed)., Statistics in Medicine 27
2008
Earlier work this paper cites.
2008
Cited alongside, same era.
2008
Cited alongside, same era.
2009
Cited alongside, same era.
2010
Cited alongside, same era.
2015
Later among the works it cites.
2015
Later among the works it cites.
2015
Later among the works it cites.
2015
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
2010
Cited alongside, same era.
2010
Cited alongside, same era.
S. J. Pan and Q. Yang, A survey on transfer learning, IEEE Transactions on Knowledge and Data Engineering 22
2010
Cited alongside, same era.
L. Torrey and J. Shavlik, Transfer learning, in Handbook of research on machine learning applications and trends: algorithms, methods, and techniques (IGI global, 2010) pp. 242–264
2010
Cited alongside, same era.
D. Pardoe and P. Stone, Boosting for regression transfer, in Proceedings of the 27th International Conference on International Conference on Machine Learning , ICML’10 (Omnipress, Madison, WI, USA, 2010) p. 863–870
2010
Cited alongside, same era.
B. Cao, S. J. Pan, Y. Zhang, D.-Y. Yeung, and Q. Yang, Adaptive transfer learning, in proceedings of the AAAI Conference on Artificial Intelligence , Vol. 24 (2010)
2010
Cited alongside, same era.
2010
Cited alongside, same era.
2010
Cited alongside, same era.
B. Iooss and P. Lemaître, A review on global sensitivity analysis methods, in Uncertainty Management in Simulation-Optimization of Complex Systems (Springer, 2015) pp. 101–122
2015
Later among the works it cites.
2016
Later among the works it cites.
2016
Later among the works it cites.
2016
Later among the works it cites.
2016
Later among the works it cites.
2018
Later among the works it cites.
2018
Later among the works it cites.
S. Mak, C.-L. Sung, X. Wang, S.-T. Yeh, Y.-H. Chang, V. R. Joseph, V. Yang, and C. F. J. J. Wu, An efficient surrogate model for emulation and physics extraction of large eddy simulations, Journal of the American Statistical Association 113
2018
Later among the works it cites.
J. E. Bernhard, J. S. Moreland, and S. A. Bass, Bayesian estimation of the specific shear and bulk viscosity of quark–gluon plasma, Nature Phys. 15
2019
Later among the works it cites.
A. Paleyes, M. Pullin, M. Mahsereci, N. Lawrence, and J. González, Emulation of physical processes with emukit, in Second Workshop on Machine Learning and the Physical Sciences, NeurIPS (2019)
2019
Later among the works it cites.
J. R. Coleman, Topics in Bayesian computer model emulation and calibration, with applications to high-energy particle collisions , Ph.D. thesis, Duke University, Department of Statistical Science (2019)
2019
Later among the works it cites.
2020
Later among the works it cites.
F. Liu, E. Wang, X.-N. Wang, N. Xu, and B.-W. Zhang, eds., The 28th International Conference on Ultra-relativistic Nucleus-Nucleus Collisions: Quark Matter 2019 , Nucl. Phys. A1005
2020
Later among the works it cites.
F. Zhuang, Z. Qi, K. Duan, D. Xi, Y. Zhu, H. Zhu, H. Xiong, and Q. He, A comprehensive survey on transfer learning, Proceedings of the IEEE 109
2020
Later among the works it cites.
J. Chen, S. Mak, V. R. Joseph, and C. Zhang, Function-on-function kriging, with applications to three-dimensional printing of aortic tissues, Technometrics 63
2021
Later among the works it cites.
G. Casella and R. L. Berger, Statistical Inference (Cengage Learning, 2021)
2021
Later among the works it cites.
2021
Later among the works it cites.
2021
Later among the works it cites.