Forwarded from Divyá Ranjan
MY COLLECTION OF SITES TO GET FREE EBOOKS
1. https://1lib.in/
2. http://gen.lib.rus.ec/
3. https://www.gutenberg.org/
4. https://www.pdfdrive.com/
5. https://archive.org/details/books
6. https://bookboon.com/
7. https://standardebooks.org/
8. https://m.feedbooks.com/
9. https://snewd.com/
10. https://www.bookrix.com/
11. https://openlibrary.org/
12. https://onemorelibrary.com/index.php/en/
1. https://1lib.in/
2. http://gen.lib.rus.ec/
3. https://www.gutenberg.org/
4. https://www.pdfdrive.com/
5. https://archive.org/details/books
6. https://bookboon.com/
7. https://standardebooks.org/
8. https://m.feedbooks.com/
9. https://snewd.com/
10. https://www.bookrix.com/
11. https://openlibrary.org/
12. https://onemorelibrary.com/index.php/en/
Information theory: A foundation for complexity science
Abstract:
Modeling and inference are central to most areas of science
and especially to evolving and complex systems. Critically,
the information we have is often uncertain and insufficient,
resulting in an underdetermined inference problem; multi-
ple inferences, models, and theories are consistent with
available information. Information theory (in particular, the
maximum information entropy formalism) provides a way
to deal with such complexity. It has been applied to numer-
ous problems, within and across many disciplines, over the
last few decades. In this perspective, we review the histori-
cal development of this procedure, provide an overview of
the many applications of maximum entropy and its exten-
sions to complex systems, and discuss in more detail some
recent advances in constructing comprehensive theory
based on this inference procedure. We also discuss efforts
at the frontier of information-theoretic inference: applica-
tion to complex dynamic systems with time-varying con-
straints, such as highly disturbed ecosystems or rapidly
changing economies.
Abstract:
Modeling and inference are central to most areas of science
and especially to evolving and complex systems. Critically,
the information we have is often uncertain and insufficient,
resulting in an underdetermined inference problem; multi-
ple inferences, models, and theories are consistent with
available information. Information theory (in particular, the
maximum information entropy formalism) provides a way
to deal with such complexity. It has been applied to numer-
ous problems, within and across many disciplines, over the
last few decades. In this perspective, we review the histori-
cal development of this procedure, provide an overview of
the many applications of maximum entropy and its exten-
sions to complex systems, and discuss in more detail some
recent advances in constructing comprehensive theory
based on this inference procedure. We also discuss efforts
at the frontier of information-theoretic inference: applica-
tion to complex dynamic systems with time-varying con-
straints, such as highly disturbed ecosystems or rapidly
changing economies.
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Forwarded from Axis of Ordinary
"…if we can generate unlimited training data for coding in particular, this suggests that *future language models will be far better at coding than anything else.*"
https://threadreaderapp.com/thread/1558347542101839873.html
https://threadreaderapp.com/thread/1558347542101839873.html
Love might be a second-order phase transition
Abstract:
The hypothesis of the human brain operation in vicinity of a critical point has been a matter of a hot debate in the recent years. The evidence for a possibility of a naturally occurring phase transition across this critical point was missing so far. Here we show that love might be an example of such second-order phase transition. This hypothesis allows to describe both love at first sight and love from liking or friendship.
https://arxiv.org/pdf/2203.13246.pdf
Abstract:
The hypothesis of the human brain operation in vicinity of a critical point has been a matter of a hot debate in the recent years. The evidence for a possibility of a naturally occurring phase transition across this critical point was missing so far. Here we show that love might be an example of such second-order phase transition. This hypothesis allows to describe both love at first sight and love from liking or friendship.
https://arxiv.org/pdf/2203.13246.pdf
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