mkocabas

####### LOSS FUNCTION #######
class MultivariateGaussianNegativeLogLikelihood(nn.Module):
    def __init__(self):
        super(MultivariateGaussianNegativeLogLikelihood, self).__init__()

    def forward(self, pred_mean, pred_var, gt):
        mu = pred_mean
        logsigma = pred_var

        mse = -0.5 * torch.sum(torch.square((gt - mu) / torch.exp(logsigma)), dim=1)

pemagrg1

import ruamel.yaml

yaml = ruamel.yaml.YAML()
data = yaml.load(open('environment.yml'))

requirements = []
for dep in data['dependencies']:
    if isinstance(dep, str):
        package, package_version, python_version = dep.split('=')
        if python_version == '0':

mbsariyildiz

def pairwise_dist (A, B):  
  """
  Computes pairwise distances between each elements of A and each elements of B.

  Args:
    A,    [m,d] matrix
    B,    [n,d] matrix

  Returns:
    D,    [m,n] matrix of pairwise distances

kevin-keraudren

Conferences in Medical Imaging/Computer Vision

MICCAI: Medical Image Computing and Computer Assisted Intervention

http://www.miccai.org/

BMVC: British Machine Vision Conference