There is a function tf.Graph.get_tensor_by_name(). For instance:
import tensorflow as tf
c = tf.constant([[1.0, 2.0], [3.0, 4.0]])
d = tf.constant([[1.0, 1.0], [0.0, 1.0]])
e = tf.matmul(c, d, name="example")
with tf.Session() as sess:
test = sess.run(e)
print e.name #example:0
test = tf.get_default_graph().get_tensor_by_name("example:0")
print test #Tensor("example:0", shape=(2, 2), dtype=float32)