<commit_before>'''

@author: <NAME>

@TODO: Implement an efficient Noisy-Max PotentialTable with sparse parametrization
    as described in http://www.ia.uned.es/~seve/publications/MAX.pdf
'''

__all__ = ['PotentialTable']

import theano
import theano.tensor as T
from discrete_pgm import DiscretePGM
import numpy as np
from expression_utils import LogSumExp
from copy import copy

class PotentialTable(object):
<commit_msg>Updated TODO<commit_after>'''

@author: <NAME>

@TODO: 

    * NoisyMax: Implement an efficient Noisy-Max PotentialTable with sparse parametrization
      as described in https://web.archive.org/web/20130622092203/http://www.ia.uned.es/~seve/publications/MAX.pdf
    
    * Particle List Message Passing: Create an efficient particle list potential table implementation
      where we use fast local map/shuffle/reduce operations to efficiently 
          * join particle list potentials (required for potential multiply/add)
          * incorporate evidence (skip / reweight all particles in the map phase to make them consistent with evidence)
          * marginalize particle lists.    
'''

__all__ = ['PotentialTable']

import theano
import theano.tensor as T
from discrete_pgm import DiscretePGM
import numpy as np
from expression_utils import LogSumExp
from copy import copy

class PotentialTable(object):

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