計劃進修PhD/Research討論區(51) 日知其所亡，月無忘其所能

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另外有興趣想留自己Research Info既巴絲, 希望可以搵到同field既巴打傾下計或者睇下有無potential collaboration, 可以係下面個google doc填自己既資料(optional)
https://docs.google.com/spreadsheets/d/1VAW9av9mt3RnUiYU7t8NhV73P7hc5mTZc1rRccket00/edit?usp=sharing

如果你想分享下報pg經驗，或者知多啲關於報pg嘅嘢，可以入去呢個word：
https://docs.google.com/document/d/1-6RuzKFOdboyqvHGpUcDhZpLz833E2m8jEi3FJfnUCI/edit

有興趣係academic 發展，做research既巴絲入黎傾下啦

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忒修斯之船 2018-1-8 12:50:18 數統電腦自學資源:

A. Maths:

Linear algebra:
ODE:
PDE:
Numerical analysis:
Optimisation: Boyd, S. & Vandenberghe, L. (2004). Convex Optimization. Cambridge University Press. URL https://www.stanford.edu/~boyd/cvxbook/
Elementary probability: Ross, S. M. (2014). A First Course in Probability (9th edition). Pearson.
Elementary stochastic processes:
Probability theory: Ross, S. M. (2014). Introduction to Probability Models (11th edition). Academic Press.
Stochastic calculus: Øksendal, B. (2003). Stochastic Differential Equations (6th edition). Universitext. Springer, Berlin, Heidelberg.
Measure-theoretic probability theory: Chung, K. L. (2000). A Course in Probability Theory (2nd edition). Academic Press.

B. Statistics:

Elementary statistics:
Linear models: Neter, J., Kutner, M. H., Nachtsheim, C. J., & Wasserman, W. (1996). Applied Linear Statistical Models (Vol. 4). Chicago: Irwin.
Bayesian inference: Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A., & Rubin, D. B. (2014). Bayesian Data Analysis (Vol. 2). Boca Raton, FL: CRC press.
Generalized Linear Model: Myers, R. H.,‎ Montgomery, D. C.,‎ Vining G. G.,‎ Robinson T. J. (2010). Generalized Linear Models: with Applications in Engineering and the Sciences (2nd Edition). Wiley.
Multilevel models: Gelman, A., & Hill, J. (2007). Data analysis using regression and multilevel hierarchical models (Vol. 1). New York, NY, USA: Cambridge University Press.
Multivariate:
Study design:
Time series: Tsay, R. S. (2010). Analysis of Financial Time Series (3rd edition). Wiley.
Categorical data analysis: Agresti, A. (2007). An Introduction to Categorical Data Analysis (2nd Edition), Wiley Series in Probability and Statistics. Wiley.
Bootstrap: Efron, B. & Tibshirani, R. (1994). An Introduction to the Bootstrap. Chapman and Hall/CRC.
Statistical inference: Casella, G. &‎ Berger, R. L. (2001). Statistical Inference (2nd Edition). Duxbury Press.
Statistical learning: Hastie, T.,‎ Tibshirani, R. & Friedman J. (2016). The Elements of Statistical Learning: Data Mining, Inference, and Prediction (2nd Edition), Springer Series in Statistics. Springer.

C. Computer Science:

Basic programming:
Information retrieval:
Computational phylogenetics:
Machine learning: Bishop, C. M. (2011). Pattern Recognition and Machine Learning. Springer.
Deep learning: Goodfellow, I., Bengio, Y. & Courville, A. (2016). Deep Learning. The MIT Press.

歡迎大家繼續擴充

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忒修斯之船 2018-1-8 12:50:52 精選papers:

Phy :
journals.aps.org/rmp/abstract/10.1103/RevModPhys.87.981
phys.sinica.edu.tw/~nano/article/e-04.pdf
Maths:
jstor.org/stable/1969529?seq=1#page_scan_tab_contents
ncbi.nlm.nih.gov/pmc/articles/PMC1063129
arxiv.org/abs/1704.07210
Econ: researchgate.net/profile/Ariel_Rubinstein2/publication/4719889_The_Electronic_Mail_Game_Strategic_Behavior_Under_Almost_Common_Knowledge/links/004635309c7e0b6a58000000.pdf
CS/EE:
statweb.stanford.edu/~candes/papers/StableRecovery.pdf
math.harvard.edu/~ctm/home/text/others/shannon/entropy/entropy.pdf
Bio:
nature.com/nbt/journal/v34/n1/full/nbt.3439.html?foxtrotcallback=true
Psychology:
journals.sagepub.com/doi/abs/10.1177/0956797611417632
cambridge.org/core/journals/behavioral-and-brain-sciences/article/weirdest-people-in-the-world/BF84F7517D56AFF7B7EB58411A554C17
nature.com/articles/s41562-017-0189-z
歡迎大家繼續擴充

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忒修斯之船 2018-1-8 12:52:28

數統電腦自學資源:

A. Maths:

Linear algebra:
ODE:
PDE:
Numerical analysis:
Optimisation: Boyd, S. & Vandenberghe, L. (2004). Convex Optimization. Cambridge University Press. URL https://www.stanford.edu/~boyd/cvxbook/
Elementary probability: Ross, S. M. (2014). A First Course in Probability (9th edition). Pearson.
Probability theory: Ross, S. M. (2014). Introduction to Probability Models (11th edition). Academic Press.
Stochastic calculus: Øksendal, B. (2003). Stochastic Differential Equations (6th edition). Universitext. Springer, Berlin, Heidelberg.
Measure-theoretic probability theory: Chung, K. L. (2000). A Course in Probability Theory (2nd edition). Academic Press.

B. Statistics:

Elementary statistics: Hogg, R. V., & Craig, A. T. (1995). Introduction to mathematical statistics.(5"" edition) (pp. 269-278). Upper Saddle River, New Jersey: Prentice Hall.
Linear models: Neter, J., Kutner, M. H., Nachtsheim, C. J., & Wasserman, W. (1996). Applied Linear Statistical Models (Vol. 4). Chicago: Irwin.
Bayesian inference: Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A., & Rubin, D. B. (2014). Bayesian Data Analysis (Vol. 2). Boca Raton, FL: CRC press.
Generalized Linear Model: Myers, R. H.,‎ Montgomery, D. C.,‎ Vining G. G.,‎ Robinson T. J. (2010). Generalized Linear Models: with Applications in Engineering and the Sciences (2nd Edition). Wiley.
Multilevel models: Gelman, A., & Hill, J. (2007). Data analysis using regression and multilevel hierarchical models (Vol. 1). New York, NY, USA: Cambridge University Press.
Multivariate: Rencher, A. C. (2003). Methods of multivariate analysis (Vol. 492). John Wiley & Sons.
Study design:
Time series: Tsay, R. S. (2010). Analysis of Financial Time Series (3rd edition). Wiley.
Categorical data analysis: Agresti, A. (2007). An Introduction to Categorical Data Analysis (2nd Edition), Wiley Series in Probability and Statistics. Wiley.
Bootstrap: Efron, B. & Tibshirani, R. (1994). An Introduction to the Bootstrap. Chapman and Hall/CRC.
Statistical inference: Casella, G. &‎ Berger, R. L. (2001). Statistical Inference (2nd Edition). Duxbury Press.
Statistical learning: Hastie, T.,‎ Tibshirani, R. & Friedman J. (2016). The Elements of Statistical Learning: Data Mining, Inference, and Prediction (2nd Edition), Springer Series in Statistics. Springer.

C. Computer Science:

Basic programming:
Information retrieval:
Computational phylogenetics:
Machine learning: Bishop, C. M. (2011). Pattern Recognition and Machine Learning. Springer.
Deep learning: Goodfellow, I., Bengio, Y. & Courville, A. (2016). Deep Learning. The MIT Press.

歡迎大家繼續擴充
:^(

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忒修斯之船 2018-1-8 12:59:09

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Elias 2018-1-8 12:59:22

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忒修斯之船 2018-1-8 13:00:11

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Elias 2018-1-8 13:00:18

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Elias 2018-1-8 13:04:36

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Elias 2018-1-8 13:08:43

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Elias 2018-1-8 13:10:57

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Elias 2018-1-8 13:11:39

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忒修斯之船 2018-1-8 13:12:15

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Elias 2018-1-8 13:12:29

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我沒有放棄 2018-1-8 13:15:34

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我沒有放棄 2018-1-8 13:16:41

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