Whats the Difference between probabilistic programming such as pyro and Belief networks? The Next CEO of Stack Overflow2019 Community Moderator ElectionWhat is difference between Bayesian Network and Belief Network?Bayes net inference in PyroFor every Bayesian Network, is there a Neural Network that gives the same output?What is the difference between a (dynamic) Bayes network and a HMM?What is difference between Bayesian Network and Belief Network?How to calculate the Probability for the Unconditional Node in the Bayesian Belief Network?Which learning algorithms to use in what order - dimensionality reduction, bayesian network structure, regression?How is the LSTM RNN forget gate calculated?How to find Neural Network ZOOs?what is difference between the DDQN and DQN?
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Whats the Difference between probabilistic programming such as pyro and Belief networks?
The Next CEO of Stack Overflow2019 Community Moderator ElectionWhat is difference between Bayesian Network and Belief Network?Bayes net inference in PyroFor every Bayesian Network, is there a Neural Network that gives the same output?What is the difference between a (dynamic) Bayes network and a HMM?What is difference between Bayesian Network and Belief Network?How to calculate the Probability for the Unconditional Node in the Bayesian Belief Network?Which learning algorithms to use in what order - dimensionality reduction, bayesian network structure, regression?How is the LSTM RNN forget gate calculated?How to find Neural Network ZOOs?what is difference between the DDQN and DQN?
$begingroup$
I heard about ubers pyro and stumbled upon this Wikipedia Artikel
As I understand a bayesian network is the same as a belief netLink to datascience StackExchange post
Does someone know how these are related?
deep-learning bayesian-networks probabilistic-programming
asked Dec 11 '18 at 15:06
Alexander VocaetAlexander Vocaet
133
$endgroup$
add a comment |
$begingroup$
I heard about ubers pyro and stumbled upon this Wikipedia Artikel
As I understand a bayesian network is the same as a belief netLink to datascience StackExchange post
Does someone know how these are related?
deep-learning bayesian-networks probabilistic-programming
asked Dec 11 '18 at 15:06
Alexander VocaetAlexander Vocaet
133
$endgroup$
add a comment |
$begingroup$
I heard about ubers pyro and stumbled upon this Wikipedia Artikel
As I understand a bayesian network is the same as a belief netLink to datascience StackExchange post
Does someone know how these are related?
deep-learning bayesian-networks probabilistic-programming
asked Dec 11 '18 at 15:06
Alexander VocaetAlexander Vocaet
133
$endgroup$
I heard about ubers pyro and stumbled upon this Wikipedia Artikel
As I understand a bayesian network is the same as a belief netLink to datascience StackExchange post
Does someone know how these are related?
deep-learning bayesian-networks probabilistic-programming
deep-learning bayesian-networks probabilistic-programming
asked Dec 11 '18 at 15:06
Alexander VocaetAlexander Vocaet
133
asked Dec 11 '18 at 15:06
Alexander VocaetAlexander Vocaet
133
asked Dec 11 '18 at 15:06
Alexander VocaetAlexander Vocaet
133
asked Dec 11 '18 at 15:06
Alexander VocaetAlexander Vocaet
133
asked Dec 11 '18 at 15:06
Alexander VocaetAlexander Vocaet
133
133
add a comment |
add a comment |
1 Answer
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A probabilistic program and a Bayesian Network are both ways of specifying probabilistic models. Any model that can be specified as a Bayesian Network can also be specified by a probabilistic program, in fact by a probabilistic program that has no control flow. Roughly
Bayes Nets == Straight line Probabilistic Programs
For example consider the Bayes Net
This Bayes Net is equivalent to the probabilistic program (in Pyro)
def model():
p_rain = pyro.param("p_rain", torch.tensor(0.2), constraint=unit_interval)
p_sprinkler = pyro.param("p_sprinkler", torch.tensor([0.4, 0.01]),
constraint=unit_interval)
p_wet = pyro.param("p_wet", torch.tensor([[0.0, 0.9], [0.8, 0.99]]),
constraint=unit_interval)
rain = pyro.sample("rain", Bernoulli(p_rain))
sprinkler = pyro.sample("sprinkler",
Bernoulli(p_sprinkler[rain.long()]))
wet = pyro.sample("wet", Bernoulli(p_wet[rain.long(), sprinkler.long()]))
More generally, probabilistic programs can contain control flow (if, for, while) and recursion. Some of these extra features are expressed in extensions to Bayes nets, e.g. some for loops can be expressed as plates in Bayes Nets.
answered Jan 11 at 2:36
FritzFritz
1162
$endgroup$
1
$begingroup$
What's the point ofp_rain? It's never used. Should it be removed, sinceraindefined further down seems to be the important version.
$endgroup$
– beldaz
Mar 24 at 23:55
add a comment |
Your Answer
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1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
$begingroup$
A probabilistic program and a Bayesian Network are both ways of specifying probabilistic models. Any model that can be specified as a Bayesian Network can also be specified by a probabilistic program, in fact by a probabilistic program that has no control flow. Roughly
Bayes Nets == Straight line Probabilistic Programs
For example consider the Bayes Net
This Bayes Net is equivalent to the probabilistic program (in Pyro)
def model():
p_rain = pyro.param("p_rain", torch.tensor(0.2), constraint=unit_interval)
p_sprinkler = pyro.param("p_sprinkler", torch.tensor([0.4, 0.01]),
constraint=unit_interval)
p_wet = pyro.param("p_wet", torch.tensor([[0.0, 0.9], [0.8, 0.99]]),
constraint=unit_interval)
rain = pyro.sample("rain", Bernoulli(p_rain))
sprinkler = pyro.sample("sprinkler",
Bernoulli(p_sprinkler[rain.long()]))
wet = pyro.sample("wet", Bernoulli(p_wet[rain.long(), sprinkler.long()]))
More generally, probabilistic programs can contain control flow (if, for, while) and recursion. Some of these extra features are expressed in extensions to Bayes nets, e.g. some for loops can be expressed as plates in Bayes Nets.
answered Jan 11 at 2:36
FritzFritz
1162
$endgroup$
1
$begingroup$
What's the point ofp_rain? It's never used. Should it be removed, sinceraindefined further down seems to be the important version.
$endgroup$
– beldaz
Mar 24 at 23:55
add a comment |
$begingroup$
A probabilistic program and a Bayesian Network are both ways of specifying probabilistic models. Any model that can be specified as a Bayesian Network can also be specified by a probabilistic program, in fact by a probabilistic program that has no control flow. Roughly
Bayes Nets == Straight line Probabilistic Programs
For example consider the Bayes Net
This Bayes Net is equivalent to the probabilistic program (in Pyro)
def model():
p_rain = pyro.param("p_rain", torch.tensor(0.2), constraint=unit_interval)
p_sprinkler = pyro.param("p_sprinkler", torch.tensor([0.4, 0.01]),
constraint=unit_interval)
p_wet = pyro.param("p_wet", torch.tensor([[0.0, 0.9], [0.8, 0.99]]),
constraint=unit_interval)
rain = pyro.sample("rain", Bernoulli(p_rain))
sprinkler = pyro.sample("sprinkler",
Bernoulli(p_sprinkler[rain.long()]))
wet = pyro.sample("wet", Bernoulli(p_wet[rain.long(), sprinkler.long()]))
More generally, probabilistic programs can contain control flow (if, for, while) and recursion. Some of these extra features are expressed in extensions to Bayes nets, e.g. some for loops can be expressed as plates in Bayes Nets.
answered Jan 11 at 2:36
FritzFritz
1162
$endgroup$
1
$begingroup$
What's the point ofp_rain? It's never used. Should it be removed, sinceraindefined further down seems to be the important version.
$endgroup$
– beldaz
Mar 24 at 23:55
add a comment |
$begingroup$
A probabilistic program and a Bayesian Network are both ways of specifying probabilistic models. Any model that can be specified as a Bayesian Network can also be specified by a probabilistic program, in fact by a probabilistic program that has no control flow. Roughly
Bayes Nets == Straight line Probabilistic Programs
For example consider the Bayes Net
This Bayes Net is equivalent to the probabilistic program (in Pyro)
def model():
p_rain = pyro.param("p_rain", torch.tensor(0.2), constraint=unit_interval)
p_sprinkler = pyro.param("p_sprinkler", torch.tensor([0.4, 0.01]),
constraint=unit_interval)
p_wet = pyro.param("p_wet", torch.tensor([[0.0, 0.9], [0.8, 0.99]]),
constraint=unit_interval)
rain = pyro.sample("rain", Bernoulli(p_rain))
sprinkler = pyro.sample("sprinkler",
Bernoulli(p_sprinkler[rain.long()]))
wet = pyro.sample("wet", Bernoulli(p_wet[rain.long(), sprinkler.long()]))
More generally, probabilistic programs can contain control flow (if, for, while) and recursion. Some of these extra features are expressed in extensions to Bayes nets, e.g. some for loops can be expressed as plates in Bayes Nets.
answered Jan 11 at 2:36
FritzFritz
1162
$endgroup$
A probabilistic program and a Bayesian Network are both ways of specifying probabilistic models. Any model that can be specified as a Bayesian Network can also be specified by a probabilistic program, in fact by a probabilistic program that has no control flow. Roughly
Bayes Nets == Straight line Probabilistic Programs
For example consider the Bayes Net
This Bayes Net is equivalent to the probabilistic program (in Pyro)
def model():
p_rain = pyro.param("p_rain", torch.tensor(0.2), constraint=unit_interval)
p_sprinkler = pyro.param("p_sprinkler", torch.tensor([0.4, 0.01]),
constraint=unit_interval)
p_wet = pyro.param("p_wet", torch.tensor([[0.0, 0.9], [0.8, 0.99]]),
constraint=unit_interval)
rain = pyro.sample("rain", Bernoulli(p_rain))
sprinkler = pyro.sample("sprinkler",
Bernoulli(p_sprinkler[rain.long()]))
wet = pyro.sample("wet", Bernoulli(p_wet[rain.long(), sprinkler.long()]))
More generally, probabilistic programs can contain control flow (if, for, while) and recursion. Some of these extra features are expressed in extensions to Bayes nets, e.g. some for loops can be expressed as plates in Bayes Nets.
answered Jan 11 at 2:36
FritzFritz
1162
edited 56 mins ago
answered Jan 11 at 2:36
FritzFritz
1162
answered Jan 11 at 2:36
FritzFritz
1162
answered Jan 11 at 2:36
FritzFritz
1162
1162
1
$begingroup$
What's the point ofp_rain? It's never used. Should it be removed, sinceraindefined further down seems to be the important version.
$endgroup$
– beldaz
Mar 24 at 23:55
add a comment |
1
$begingroup$
What's the point ofp_rain? It's never used. Should it be removed, sinceraindefined further down seems to be the important version.
$endgroup$
– beldaz
Mar 24 at 23:55
1
1
$begingroup$
What's the point of
p_rain? It's never used. Should it be removed, since rain defined further down seems to be the important version.$endgroup$
– beldaz
Mar 24 at 23:55
$begingroup$
What's the point of
p_rain? It's never used. Should it be removed, since rain defined further down seems to be the important version.$endgroup$
– beldaz
Mar 24 at 23:55
add a comment |
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