Question

Formula for Cross-Entropy Loss for Vector Inputs

score 19 · Answer 1 · 2024-03-29T08:59:14.700000

19

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Formula for Cross-Entropy Loss for Vector Inputs

Published on 29 March 2024 at 08:59

score 39 · Answer 2 · 2024-03-12T11:04:20.060000

39

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Medical Binary Classification probability : BCE vs CrossEntropy

Published on 12 March 2024 at 11:04

score 36 · Answer 3 · 2024-03-09T11:51:45.640000

36

Views

Tensorflow: Incompatible shapes: [1,896] vs. [1,32] [[{{node LogicalAnd_3}}]] [Op:__inference_one_step_on_iterator_6201]

Published on 09 March 2024 at 11:51

score 45 · Answer 4 · 2024-02-26T19:40:05.673000

45

Views

Accessing the N values of PyTorch's Cross-Entropy loss function

Published on 26 February 2024 at 19:40

score 22 · Answer 5 · 2024-02-20T13:23:29.260000

22

Views

CrossEntropyLoss loss function type problem

Published on 20 February 2024 at 13:23

score 24 · Answer 6 · 2024-02-08T08:15:15.973000

24

Views

Why categorical_crossentropy gives 16?

Published on 08 February 2024 at 08:15

score 22 · Answer 7 · 2024-01-30T20:56:50.860000

22

Views

Is there an easy way to replace fmincon with the cross-entropy method for optimization problems

Published on 30 January 2024 at 20:56

score 59 · Answer 8 · 2024-01-06T03:15:53.573000

59

Views

Pytorch's `binary_cross_entropy` seems to implement ln(0) = -100. Why?

Published on 06 January 2024 at 03:15

score 51 · Answer 9 · 2024-01-05T03:44:28.917000

51

Views

What causes this model to not improve?

Published on 05 January 2024 at 03:44

score 65 · Answer 10 · 2023-12-11T02:50:54.703000

65

Views

Suppose logits are a 34 matrix, and the target is a 13, how is cross-entropy loss calculated mathematically?

Published on 11 December 2023 at 02:50

score 155 · Answer 11 · 2023-11-22T20:12:21.817000

155

Views

Problem replicating a comparison between CE and MSE

Published on 22 November 2023 at 20:12

score 190 · Answer 12 · 2023-11-13T16:13:58.310000

190

Views

Pytorch CrossEntropy Loss, getting error: "RuntimeError: Boolean value of Tensor with more than one value is ambiguous"

Published on 13 November 2023 at 16:13

score 71 · Answer 13 · 2023-11-13T15:13:10.093000

71

Views

Tensorflow binary classifier with weighted loss function - Why does train history accuracy doesn't match train accuracy?

Published on 13 November 2023 at 15:13

score 270 · Answer 14 · 2023-10-21T16:53:37.573000

270

Views

How to do PyTorch F.cross_entropy?

Published on 21 October 2023 at 16:53

score 156 · Answer 15 · 2023-10-14T22:45:20.237000

156

Views

Can you use perplexity to guess the language of a document?

Published on 14 October 2023 at 22:45

score 237 · Answer 16 · 2023-10-08T14:53:09.910000

237

Views

nn.BCELoss() is giving very bad results unlike BCEWithLogitsLoss

Published on 08 October 2023 at 14:53

score 60 · Answer 17 · 2023-10-01T08:18:17.803000

60

Views

Calculating Chao-Shen corrected Jensen-Shannon Divergence

Published on 01 October 2023 at 08:18

score 39 · Answer 18 · 2023-09-29T07:58:27.067000

39

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KL divergence corrected for limited sample size bias

Published on 29 September 2023 at 07:58

score 63 · Answer 19 · 2023-09-06T19:42:32.140000

63

Views

Why am I getting the wrong answer using pyTorch's cross-entropy?

Published on 06 September 2023 at 19:42

score 28 · Answer 20 · 2023-08-25T16:36:42.487000

28

Views

Find mathematical interpretation of loss function and back propagation

Published on 25 August 2023 at 16:36

List Question

Formula for Cross-Entropy Loss for Vector Inputs

Medical Binary Classification probability : BCE vs CrossEntropy

Tensorflow: Incompatible shapes: [1,896] vs. [1,32] [[{{node LogicalAnd_3}}]] [Op:__inference_one_step_on_iterator_6201]

Accessing the N values of PyTorch's Cross-Entropy loss function

CrossEntropyLoss loss function type problem

Why categorical_crossentropy gives 16?

Is there an easy way to replace fmincon with the cross-entropy method for optimization problems

Pytorch's `binary_cross_entropy` seems to implement ln(0) = -100. Why?

What causes this model to not improve?

Suppose logits are a 34 matrix, and the target is a 13, how is cross-entropy loss calculated mathematically?

Problem replicating a comparison between CE and MSE

Pytorch CrossEntropy Loss, getting error: "RuntimeError: Boolean value of Tensor with more than one value is ambiguous"

Tensorflow binary classifier with weighted loss function - Why does train history accuracy doesn't match train accuracy?

How to do PyTorch F.cross_entropy?

Can you use perplexity to guess the language of a document?

nn.BCELoss() is giving very bad results unlike BCEWithLogitsLoss

Calculating Chao-Shen corrected Jensen-Shannon Divergence

KL divergence corrected for limited sample size bias

Why am I getting the wrong answer using pyTorch's cross-entropy?

Find mathematical interpretation of loss function and back propagation

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