Unanswered 'loss' Questions

3

votes

1answer

105 views

How to perform back-propagation in Decoupled Neural Interfaces?

I am attempting to create a fully decoupled feed-forward neural network by using decoupled neural interfaces (DNIs) as explained in the paper Decoupled Neural Interfaces using Synthetic Gradients (...

asked Dec 30 '16 at 1:42

Brian Sharp

411 bronze badge

2

votes

1answer

34 views

Data scan not making sense for coco dataset

I am doing a simple scan to see how dataset size affects training. Basically, I took 10% of the coco dataset and trained a yolov3 net (from scratch) to just look for people. Then I took 20% of the ...

training yolo loss

asked Mar 3 '20 at 14:11

Ivan Viti

212 bronze badges

2

votes

0answers

19 views

Why is the loss of one of the outputs of a model with multiple outputs increasing while the others are decreasing?

I'm a newbie in neural networks. I'm trying to fit my neural network that has 3 different outputs: semantic segmentation, box mask and box coordinates. When my model is training, the loss of ...

machine-learning convolutional-neural-networks training overfitting loss

asked Feb 20 '20 at 15:27

João Castilho

1313 bronze badges

1

vote

1answer

52 views

Can someone explain me what does this loss curve says?

I was training a CNN model on TensorFlow. After a while I came back and saw this loss curve: The green curve is training loss and the gray one is validation loss. I know that before epoch 394 the ...

convolutional-neural-networks training overfitting loss

asked Dec 14 '20 at 9:30

Sepehr Golestanian

114 bronze badges

1

vote

0answers

25 views

WGAN-GP Loss formalization

I have to write the formalization of the loss function of my network, built following the WGAN-GP model. The discriminator takes 3 consecutive images as input (such as 3 consecutive frames of a video) ...

deep-learning generative-adversarial-networks loss wasserstein-metric

asked Nov 4 '20 at 12:49

Gibser

112 bronze badges

1

vote

0answers

34 views

Why does loss and accuracy for a multi label classification ann does not change overtime?

I have run into a strange behavior of my multi label classification ANN ...

neural-networks accuracy loss

asked Aug 18 '20 at 6:22

User2741

112 bronze badges

1

vote

0answers

39 views

LSTM - MAPE Loss Function gives Better Results when Data is De-Scaled before Loss Calculation

I am building an LSTM for predicting a price chart. MAPE resulted in the best loss function compared to ...

long-short-term-memory loss-functions weights loss scalability

asked Jun 9 '20 at 7:22

user134132523

111 bronze badge

1

vote

0answers

141 views

what will be the best loss function for unet to predict the each pixel values?

I'm predicting the used 9 pictures to predict the last picture so (40,40,9) -> unet -> (40,40,1) but as you see the predict picture It's not just a mask(0or 1) its float so which loss function ...

loss-functions image-segmentation loss

asked May 12 '20 at 0:37

slowmonk

1512 bronze badges

1

vote

1answer

68 views

Do smaller loss values during DQN training produce better policies?

During the training of DQN, I noticed that the model with prioritized experience replay (PER) had a smaller loss in general compared to a DQN without PER. The mean squared loss was an order of ...

reinforcement-learning dqn loss

asked May 11 '20 at 16:30

calveeen

1,1363 silver badges13 bronze badges

1

vote

0answers

44 views

How MSE should be appliead with multi target deep network?

I'm having a problem understanding how the MSE should be used when working with a multidimensional target, e.g 3 dimensiones. (My outputs are continuois values, not categorical) Let us say I have a ...

deep-learning loss-functions regression loss mean-squared-error

asked Apr 28 '20 at 11:26

Cla

234 bronze badges

1

vote

0answers

28 views

Crossing of training and validation loss

During training of my models I often encounter the following situation about training (green) and validation (gray) loss: Initially, the validation loss is significantly lower than the training loss. ...

loss

asked Feb 18 '20 at 10:58

Feodoran

1563 bronze badges

1

vote

0answers

29 views

Deduce properties of the loss functions from the training loss curves

I have two convex, smooth loss functions to minimise. During the training (a very simple model) using batch SGD (with tuned optimal learning rate for each loss function), I observe that the (log) loss ...

training loss-functions loss

asked Jan 5 '20 at 0:42

SiXUlm

1112 bronze badges

0

votes

0answers

33 views

How to evaluate the learning effect of reinforcement learning

I am a student who has just started learning about reinforcement learning. Is there a way to evaluate the learning effect of reinforcement learning that can be actually calculated from information ...

reinforcement-learning policies loss

asked Jan 8 at 15:04

ground clown

931 bronze badge

0

votes

0answers

15 views

Loss function for better class separability in multi class classification

So I am trying to enforce better separability in my deep learning model and was wondering what I can use besides cross entropy loss to do that? Could maybe using logarithm with different basis in ...

classification loss-functions loss cross-entropy

asked Oct 8 '20 at 17:55

GreatDuke

101

0

votes

0answers

40 views

Variance of the Gaussian policy is not decreasing while training the agent using Soft Actor-Critic method

I've written my own version of SAC(v2) for a problem with continuous action space. While training, the losses for the value network and both q functions steadily decrease down to 0.02-0.03. The loss ...

reinforcement-learning tensorflow actor-critic-methods loss

asked Oct 3 '20 at 12:45

Silence Templar

11 bronze badge

0

votes

0answers

44 views

Non-trainable regularizer in loss function

I train a fully convoluted network for semantic segmentation. To each convolution blocks, I associate a module pruning feature maps to reduce the quantity of information generated by the network. From ...

convolutional-neural-networks loss-functions regularization loss

asked Jul 24 '20 at 7:14

JrCaspian

1311 bronze badge

0

votes

0answers

41 views

VAE KL divergence loss decreases really fast

I am new to training VAEs and I am using it on some 16x16 images, that contains some images from a physics experiment with one or 2 events i.e. the images are mainly black, except for one or 2 regions ...

variational-autoencoder loss

asked Jun 28 '20 at 1:03

BillKet

1512 bronze badges

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Questions tagged [loss]

How to perform back-propagation in Decoupled Neural Interfaces?

Data scan not making sense for coco dataset

Why is the loss of one of the outputs of a model with multiple outputs increasing while the others are decreasing?

Can someone explain me what does this loss curve says?

WGAN-GP Loss formalization

Why does loss and accuracy for a multi label classification ann does not change overtime?

LSTM - MAPE Loss Function gives Better Results when Data is De-Scaled before Loss Calculation

what will be the best loss function for unet to predict the each pixel values?

Do smaller loss values during DQN training produce better policies?

How MSE should be appliead with multi target deep network?

Crossing of training and validation loss

Deduce properties of the loss functions from the training loss curves

How to evaluate the learning effect of reinforcement learning

Loss function for better class separability in multi class classification

Variance of the Gaussian policy is not decreasing while training the agent using Soft Actor-Critic method

Non-trainable regularizer in loss function

VAE KL divergence loss decreases really fast

Hot Network Questions

Questions tagged [loss]

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