cliques_to_jtree <- function(cliques, ns) {
  stop("needs translation")
  #   function [jtree, root, B, w] = cliques_to_jtree(cliques, ns)
  # % MK_JTREE Make an optimal junction tree.
  # % [jtree, root, B, w] = mk_jtree(cliques, ns)
  # %
  # % A junction tree is a tree that satisfies the jtree property, which says:
  # % for each pair of cliques U,V with intersection S, all cliques on the path between U and V
  # % contain S. (This ensures that local propagation leads to global consistency.)
  # %
  # % We can create a junction tree by computing the maximal spanning tree of the junction graph.
  # % (The junction graph connects all cliques, and the weight of an edge (i,j) is
  # % |C(i) intersect C(j)|, where C(i) is the i'th clique.)
  # %
  # % The best jtree is the maximal spanning tree which minimizes the sum of the costs on each edge,
  # % where cost(i,j) = w(C(i)) + w(C(j)), and w(C) is the weight of clique C,
  # % which is the total number of values C can take on.
  # %
  # % For details, see
  # %  - Jensen and Jensen, "Optimal Junction Trees", UAI 94.
  # %
  # % Input:
  # %  cliques{i} = nodes in clique i
  # %  ns(i) = number of values node i can take on
  # % Output:
  # %  jtree(i,j) = 1 iff cliques i and j aer connected
  # %  root = the clique that should be used as root
  # %  B(i,j) = 1 iff node j occurs in clique i
  # %  w(i) = weight of clique i



  # num_cliques = length(cliques);
  # w = zeros(num_cliques, 1);
  # B = sparse(num_cliques, 1);
  # for i=1:num_cliques
  #   B(i, cliques{i}) = 1;
  #   w(i) = prod(ns(cliques{i}));
  # end


  # % C1(i,j) = length(intersect(cliques{i}, cliques{j}));
  # % The length of the intersection of two sets is the dot product of their bit vector representation.
  # C1 = B*B';
  # C1 = setdiag(C1, 0);

  # % C2(i,j) = w(i) + w(j)
  # num_cliques = length(w);
  # W = repmat(w, 1, num_cliques);
  # C2 = W + W';
  # C2 = setdiag(C2, 0);

  # jtree = sparse(minimum_spanning_tree(-C1, C2)); % Using -C1 gives *maximum* spanning tree

  # % The root is arbitrary, but since the first pass is towards the root,
  # % we would like this to correspond to going forward in time in a DBN.
  # root = num_cliques;
}