Xing Wang b6f130aa70 try to enable uncertainty for lr loss (#17236) ... Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/17236 Following the paper in https://papers.nips.cc/paper/7141-what-uncertainties-do-we-need-in-bayesian-deep-learning-for-computer-vision.pdf, approximate the classification case with the regression formulation. For the LRLoss, add penalty based on the variance and regularization on the variance with a tunable parameter lambda. Reviewed By: chocjy Differential Revision: D14077106 fbshipit-source-id: 4405d8995cebdc7275a0dd07857d32a8915d78ef		2019-04-11 07:35:19 -07:00
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__init__.py
adaptive_weight.py
add_bias.py
arc_cosine_feature_map.py
batch_distill_lr_loss.py
batch_lr_loss.py	try to enable uncertainty for lr loss (#17236)	2019-04-11 07:35:19 -07:00
batch_mse_loss.py
batch_normalization.py
batch_sigmoid_cross_entropy_loss.py
batch_softmax_loss.py
blob_weighted_sum.py
bucket_weighted.py
build_index.py
concat.py
constant_weight.py
conv.py
dropout.py	add dropout during eval (#17549)	2019-02-28 23:21:29 -08:00
fc.py
fc_without_bias.py
feature_sparse_to_dense.py	Revert D13551909: [fbcode] logdevice for generic feature type	2019-01-25 00:33:06 -08:00
functional.py
gather_record.py
homotopy_weight.py
label_smooth.py
last_n_window_collector.py
layer_normalization.py
layers.py
margin_rank_loss.py
merge_id_lists.py
pairwise_similarity.py
position_weighted.py
random_fourier_features.py
reservoir_sampling.py
sampling_train.py
sampling_trainable_mixin.py
select_record_by_context.py
semi_random_features.py
sparse_feature_hash.py
sparse_lookup.py	Resubmit: Set the correct engine name for position weighted pooling when fp16 is used for training	2018-11-27 14:51:56 -08:00
split.py
tags.py
uniform_sampling.py