- 27 Feb, 2017 1 commit
-
-
Evgeniy Fominov authored
-
- 25 Feb, 2017 2 commits
-
-
Davis King authored
-
Ehsan Azar authored
-
- 23 Feb, 2017 1 commit
-
-
Adam Geitgey authored
-
- 22 Feb, 2017 6 commits
-
-
Davis King authored
-
Davis King authored
-
Davis King authored
-
Davis King authored
-
Davis King authored
-
Davis King authored
-
- 21 Feb, 2017 2 commits
-
-
Davis King authored
-
Davis King authored
-
- 19 Feb, 2017 5 commits
-
-
Davis King authored
-
Davis King authored
-
Davis King authored
-
Davis E. King authored
-
Davis King authored
-
- 16 Feb, 2017 4 commits
-
-
Davis King authored
-
Davis King authored
-
Davis King authored
-
Davis King authored
-
- 14 Feb, 2017 1 commit
-
-
Kyle McDonald authored
-
- 13 Feb, 2017 7 commits
-
-
Davis King authored
-
Davis King authored
-
Davis King authored
-
Davis King authored
-
Davis King authored
-
Davis King authored
-
Davis King authored
-
- 12 Feb, 2017 7 commits
-
-
Davis King authored
-
Davis King authored
-
Davis King authored
-
Davis King authored
-
Davis King authored
-
Davis King authored
-
Davis King authored
-
- 11 Feb, 2017 1 commit
-
-
Davis King authored
-
- 10 Feb, 2017 1 commit
-
-
Davis King authored
-
- 09 Feb, 2017 1 commit
-
-
Davis King authored
-
- 07 Feb, 2017 1 commit
-
-
Dennis Francis authored
* feature_addition : Mean squared loss layer for multiple output (#404) * Added loss_mean_squared_multioutput layer to support multiple outputs. * Also added a corresponding test case to test a single variable regression with multiple outputs. * Added error checks on truth argument Added assert statements to check that truth argument in compute_loss_value_and_gradient() method contains matrices of correct dimension relative to the output tensor's size. Also the requirements on argument truth to the abstract documentation.
-