## Search found 15 matches

- Wed Apr 29, 2020 3:44 pm
- Forum: GeNIe
- Topic: Crash/error upon inference in a dynamic Bayesian network
- Replies:
**28** - Views:
**3997**

### Re: Crash/error upon inference in a dynamic Bayesian network

Okay, thank you. I have now more or less converged on a definitive version of my network, but when I try to launch an inference on 200 slices with observations of one node (Bit) on each slice via java code, it crashes after a few minutes with the exception "bad allocation". I use Likelihood Sampling...

- Tue Apr 28, 2020 9:36 am
- Forum: GeNIe
- Topic: Crash/error upon inference in a dynamic Bayesian network
- Replies:
**28** - Views:
**3997**

### Re: Crash/error upon inference in a dynamic Bayesian network

Hi, Okay, I understand how you proceed, but that still seems a strange and extremely inefficient way of computing the log-likelihood. Why adding the observations one at a time? Since a single one influence the inferred state of both the nodes before and after it, putting in partial obsevation would ...

- Tue Apr 21, 2020 10:37 am
- Forum: GeNIe
- Topic: Crash/error upon inference in a dynamic Bayesian network
- Replies:
**28** - Views:
**3997**

### Re: Crash/error upon inference in a dynamic Bayesian network

Hi, I read your answer about the calculus of P(e), and I don't get why you need one inference call for each evidence node. Here is how I calculate P(e): I do one call of inference without any evidence. This call gives me all the theoretical marginal probabilities of the network. Then, I sum on each ...

- Mon Apr 20, 2020 3:42 pm
- Forum: GeNIe
- Topic: Crash/error upon inference in a dynamic Bayesian network
- Replies:
**28** - Views:
**3997**

### Re: Crash/error upon inference in a dynamic Bayesian network

Hi, Thanks for your reply. I've come across another thing I don't understand : sometimes, when I use EPIS sammpling inference via SMILE, I get NaNs for some node values. I get these only when the network has a consistent size, and I've solved it by increasing the number of samples from 1K to 1M, but...

- Fri Apr 17, 2020 8:58 am
- Forum: GeNIe
- Topic: Crash/error upon inference in a dynamic Bayesian network
- Replies:
**28** - Views:
**3997**

### Re: Crash/error upon inference in a dynamic Bayesian network

Yes, but how do you calculate P(e). I know LogLikelihood is the sum of the logarithm of the probabilities of the evidence given the parameters, but the probability of the evidence may be calculated in different ways. I want to know how you calculate it. I calculate it as the theoretical probability ...

- Thu Apr 16, 2020 2:56 pm
- Forum: GeNIe
- Topic: Crash/error upon inference in a dynamic Bayesian network
- Replies:
**28** - Views:
**3997**

### Re: Crash/error upon inference in a dynamic Bayesian network

I would like to know which formula exactly you use to calculate the LogLikelihood, because I'd like to compare the results of my own implementation of EM to yours. I learn the same parameters in the end, but my LogLikelihood is not the same.

- Wed Apr 01, 2020 2:47 pm
- Forum: GeNIe
- Topic: Crash/error upon inference in a dynamic Bayesian network
- Replies:
**28** - Views:
**3997**

### Re: Crash/error upon inference in a dynamic Bayesian network

That's right, I forgot about triangularization. Considering the complexity of my graph, pretty much everything within a slice is connected, so it is indeed very complex to estimate memory usage. I need to not use junction tree in my network, whether for learning or inference. It is very annoying tha...

- Wed Apr 01, 2020 8:47 am
- Forum: GeNIe
- Topic: Crash/error upon inference in a dynamic Bayesian network
- Replies:
**28** - Views:
**3997**

### Re: Crash/error upon inference in a dynamic Bayesian network

Hi, I know how a junction tree is formed, but even when I estimate the number and size of the cliques in a very pessimistic way, the real memory usage is always a multiple of that. Here is how I estimate it : for each node of each slice, I consider all of its neighbours along itself as one clique, t...

- Tue Mar 31, 2020 8:48 am
- Forum: GeNIe
- Topic: Crash/error upon inference in a dynamic Bayesian network
- Replies:
**28** - Views:
**3997**

### Re: Crash/error upon inference in a dynamic Bayesian network

Hi, Thank you for your answer. I was highly suspecting it, but it surprises me a bit that the EM takes that much memory, as the inference doesn't need so much when using a sampling algorithm. I can do inference on my network with 160 slices, and it only takes a few hundred MB, while the EM would nee...

- Thu Mar 26, 2020 10:33 am
- Forum: GeNIe
- Topic: Crash/error upon inference in a dynamic Bayesian network
- Replies:
**28** - Views:
**3997**

### Re: Crash/error upon inference in a dynamic Bayesian network

Hi, Concerning the threshold on the ratio of log likelihood from two subsequent iterations, what is its value? I'd be glad if you could tell me why EM doesn't work with my network, but what I seek is a general answer, not one specific to this network, as it isn't a final version, just the current on...

- Tue Mar 24, 2020 9:32 am
- Forum: GeNIe
- Topic: Crash/error upon inference in a dynamic Bayesian network
- Replies:
**28** - Views:
**3997**

### Re: Crash/error upon inference in a dynamic Bayesian network

Hi, I understand well the complexity of the network and how to manage it. What I am asking is information on the complexity and the memory needs of the EM algorithm, which I can't estimate. It seems to be multiples of what is needed for inference, as all approximate inference algorithms work fine on...

- Fri Mar 20, 2020 3:28 pm
- Forum: GeNIe
- Topic: Crash/error upon inference in a dynamic Bayesian network
- Replies:
**28** - Views:
**3997**

### Re: Crash/error upon inference in a dynamic Bayesian network

Hi, The data set I attached was just a trivial one featuring only one observation, the real one will contain thousands of them. I tried learning on this trivial data set in order to check if learning worked, and it didn't. I am currently trying to reduce more and more memory consumption, but I don't...

- Thu Mar 19, 2020 12:14 pm
- Forum: GeNIe
- Topic: Crash/error upon inference in a dynamic Bayesian network
- Replies:
**28** - Views:
**3997**

### Re: Crash/error upon inference in a dynamic Bayesian network

Hi, I have modified my network to reduce the CPT of the variables while retaining an equivalent network. Here is my new network: NetworkCPTReduced.xdsl There are no longer crash problems caused by memory when doing inference. However, I still have either crashes or the "EM: inference cannot be perfo...

- Mon Mar 16, 2020 9:48 am
- Forum: GeNIe
- Topic: Crash/error upon inference in a dynamic Bayesian network
- Replies:
**28** - Views:
**3997**

### Re: Crash/error upon inference in a dynamic Bayesian network

JsmileCode.txt Hi, Thank you for your answer. I know my network is quite big, but, actually, it is only a first version, with relatively few connections, so I knew exact inference would be a bit complicated. Also, the only observation is the Bit value, everything else has to be inferred, as it is t...

- Fri Mar 13, 2020 5:45 pm
- Forum: GeNIe
- Topic: Crash/error upon inference in a dynamic Bayesian network
- Replies:
**28** - Views:
**3997**

### Crash/error upon inference in a dynamic Bayesian network

Hello, I am using GeNIe and SMILE in my PhD thesis in telecommunications. I am trying to learn the frame structure of a protocol by using a dynamic Bayesian network. I have designed the network, which contains eight nodes, each with a few dozen states, and unrolled on a few hundred slices. Here is m...