01 2019 档案
摘要:draw a topic h and then draw independent xfrom multinomial distribution A paper can have several topics, and each topics has different proportions O i
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摘要:(unfinished)
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摘要:take log to Normal distribution, it's L2 loss, which might be the cause of the blurry results of VAE interpreting the meaning of latent vars is diffic
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摘要:conent in green box difficult to solve https://www.youtube.com/watch?v=btr1poCYIzw&t=60s
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摘要:p_bar(x) = p(x,e) p(x) is p(x|e) p_bar is hard to estimate, but p(x) is easy and p(x) \propotion p_bar q is easier for sampling, while we cant sample
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2018 10-708 (CMU) Probabilistic Graphical Models {Lecture 11} [CRF (Cont'd) + Intro to Topic Models]
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摘要:between tags and words, there's table 1. between tags, there's table 2. combine the two tables, p(...) to get the results. MRF: factors of the tables
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摘要:
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摘要:Not in the frontier of research, but the results are used commonly now. X_{k+1} - X_n are known, to calculate the joint probability, we have to do inf
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摘要:DGM ignores sometimes the latent variable know parts of the proteins' states, and the corr relationships, how would other proteins's state probably be
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摘要:https://kayhan.dbmi.pitt.edu/sites/default/files/lecture2.pdf P(sequence) given both dices are fair x2 → x4 ↗ ↘ x1 x5 ↘ ↗ x3 P(x5) = P(X1) P(X2|X1) P(
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摘要:https://www.cs.cmu.edu/~epxing/Class/10708-17/slides/lecture1-Introduction.pdf Computational and CS orientated => DK and NF's book Statistical and eas
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摘要:GP is a kind of programming that will generate code for you at compile time. The core is to seperate algorithms from the data structure, and we do som
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摘要:first, install opcv4, the newest one. but brew install opencv will only get a version 3, Another way is to use source code and compile it locally, but
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摘要:only use them with heap memory. never ever apply them to stack try to avoid using "new and delete" if you can use shared or unique ptr delete the a_pt
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摘要:https://en.cppreference.com/w/cpp/language/range-for every object has a pointer to itsleft. stack operations are very quick it's computationally expen
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