ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization | Paper Citation Record

Observation 774b46cc-f6fa-4d52-a4d5-b17781c2d11e · outbound

This paper cites Abraham and N.

ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization Abraham and N

Reference 1

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Observation 73be9572-4a81-4a9d-b60c-050500bd4b6a · outbound

This paper cites Deep Learning using Rectified Linear Units (ReLU).

ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization Deep Learning using Rectified Linear Units (ReLU)

Reference 2

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Observation ca7dc0e2-6b02-48ef-acc1-e61d0cea761d · outbound

This paper cites Alsallakh, A.

ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization Alsallakh, A

Reference 3

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This paper cites Alsallakh, A.

ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization Alsallakh, A

Reference 4

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Observation 0e6cb917-6419-40f6-90b5-187ca4e1ac4a · outbound

This paper cites Building Efficient ConvNets using Redundant Feature Pruning.

ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization Building Efficient ConvNets using Redundant Feature Pruning

Reference 5

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ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization Unresolved cited work

Reference 6

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ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization Unresolved cited work

Reference 7

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Observation 1985c423-d63e-44a1-9261-d75d840deb57 · outbound

This paper cites Belcher, A.

ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization Belcher, A

Reference 8

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Observation 0277976f-9f5e-4c89-bbe9-584b9fc133c8 · outbound

This paper cites Bellgardt, C.

ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization Bellgardt, C

Reference 9

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Observation 9b003ad6-91ef-45ca-a7eb-fa2676150505 · outbound

This paper cites nearest neighbor.

ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization nearest neighbor

Reference 10

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Observation e2023d62-83dc-4fe5-87ef-4d9079a34572 · outbound

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ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization Unresolved cited work

Reference 11

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Observation f4669cb9-47ea-4541-8044-d6323ac96e85 · outbound

This paper cites Bilal, A.

ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization Bilal, A

Reference 12

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Observation fabe596e-cfd6-453f-9452-c5c9a6770051 · outbound

This paper cites Carter, Z.

ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization Carter, Z

Reference 13

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Observation bb82af79-71b0-447c-8e7b-e610dfc85b5d · outbound

This paper cites Catmull and R.

ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization Catmull and R

Reference 14

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Observation cc63a3a7-9742-4bdd-b5ad-21631eb9dd3d · outbound

This paper cites Transformer Explainer: Interactive Learning of Text-Generative Models.

ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization Transformer Explainer: Interactive Learning of Text-Generative Models

Reference 15

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Observation cd3baf99-68a9-4a0a-a3e7-c6fe7fdc5f54 · outbound

This paper cites Chung, S.

ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization Chung, S

Reference 16

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Observation 53ca02fd-995e-4b92-a9c6-10d0a484615c · outbound

This paper cites Clevert, T.

ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization Clevert, T

Reference 17

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ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization Unresolved cited work

Reference 18

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Observation e98f2839-43d8-4f2a-ad0f-64525a3d3bc1 · outbound

This paper cites Eiglsperger, M.

ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization Eiglsperger, M

Reference 19

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Observation 91ce31e3-4e8e-4634-a64c-148a002fb8e2 · outbound

This paper cites Erhan, Y.

ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization Erhan, Y

Reference 20

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Observation 2cb5cc44-49df-4721-bdfd-b1a3927a51a1 · outbound

This paper cites Fong and A.

ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization Fong and A

Reference 21

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Observation 6afc419a-5cc4-4bf5-9e31-38ee3a1ecb23 · outbound

This paper cites Black-box Error Diagnosis in Deep Neural Networks for Computer Vision: a Survey of Tools.

ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization Black-box Error Diagnosis in Deep Neural Networks for Computer Vision: a Survey of Tools

Reference 22

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Observation 4bbb71a6-2174-4c13-a6a7-6cd9c43bf638 · outbound

This paper cites Ghorbani, J.

ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization Ghorbani, J

Reference 23

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Observation ede090c4-7903-48a4-b25b-41473e791507 · outbound

This paper cites Ghosh, C.

ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization Ghosh, C

Reference 24

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Observation 868ff8d6-432c-4b8d-9090-51a0f5fd3ad8 · outbound

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ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization Unresolved cited work

Reference 25

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Observation df5d73f5-14b8-4b73-9c50-3b8b60e64df2 · outbound

This paper cites Görtler, F.

ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization Görtler, F

Reference 27

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Observation 09daf5ba-8899-452d-9c41-cee46ce2f597 · outbound

This paper cites Granziol, X.

ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization Granziol, X

Reference 28

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ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization Unresolved cited work

Reference 29

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Observation f91af4ea-fa21-40b0-a90d-c5ed34dc6bc1 · outbound

This paper cites Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification.

ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification

Reference 30

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Observation 78e8533d-47c0-4d03-9de0-29ea3011b8aa · outbound

This paper cites Deep Curvature Suite.

ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization Deep Curvature Suite

Reference 31

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This paper cites From Tinkering to Engineering: Measurements in Tensorflow Playground.

ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization From Tinkering to Engineering: Measurements in Tensorflow Playground

Reference 32

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Observation aa0bba05-b078-436e-912f-6625fda342fc · outbound

This paper cites Hohman, H.

ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization Hohman, H

Reference 33

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Observation f45b2e80-9dee-480e-9141-206e3c1c887e · outbound

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ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization Unresolved cited work

Reference 35

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Observation 1f7409ef-7b0f-49e3-9028-917b579e99db · outbound

This paper cites Huang, A.

ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization Huang, A

Reference 36

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ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization Unresolved cited work

Reference 37

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This paper cites Horoi, J.

ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization Horoi, J

Reference 38

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ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization Unresolved cited work

Reference 39

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This paper cites Kahng, P.

ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization Kahng, P

Reference 40

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ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization Unresolved cited work

Reference 42

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ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization Unresolved cited work

Reference 43

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This paper cites Self-Normalizing Neural Networks.

ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization Self-Normalizing Neural Networks

Reference 44

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This paper cites Kolesnikov, A.

ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization Kolesnikov, A

Reference 45

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This paper cites Krizhevsky, I.

ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization Krizhevsky, I

Reference 46

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This paper cites Kapoor, B.

ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization Kapoor, B

Reference 47

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ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization Unresolved cited work

Reference 48

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This paper cites Diffusion Explainer: Visual Explanation for Text-to-image Stable Diffusion.

ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization Diffusion Explainer: Visual Explanation for Text-to-image Stable Diffusion

Reference 49

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ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization Unresolved cited work

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ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization Unresolved cited work

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ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization Unresolved cited work

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This paper cites Ledig, L.

ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization Ledig, L

Reference 53

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ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization Unresolved cited work

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ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization Unresolved cited work

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This paper cites Ma´ckiewicz and W.

ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization Ma´ckiewicz and W

Reference 56

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ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization Unresolved cited work

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This paper cites Mordvintsev, C.

ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization Mordvintsev, C

Reference 59

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This paper cites Nguyen, J.

ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization Nguyen, J

Reference 60

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ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization Unresolved cited work

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ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction

Reference 62

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ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization Unresolved cited work

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ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization Unresolved cited work

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ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization Pelleg and A

Reference 65

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ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization Unresolved cited work

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ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization Pezzotti, T

Reference 67

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ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization Pühringer, A

Reference 68

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Reference 69

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Reference 70

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This paper cites Rathore, N.

ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization Rathore, N

Reference 71

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This paper cites Redmon and A.

ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization Redmon and A

Reference 72

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ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization Pezzotti, T

Reference 73

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ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization Rosenfeld, M

Reference 74

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ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization Schorr, P

Reference 75

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This paper cites https://pypi.org/.

ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization https://pypi.org/

Reference 76

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ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization Learning Transferable Visual Models From Natural Language Supervision

Reference 77

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ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization Sultana, A

Reference 78

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ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization Talbot, B

Reference 79

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Reference 80

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ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization Deep Domain Confusion: Maximizing for Domain Invariance

Reference 81

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Reference 82

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ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization Seifert, A

Reference 83

Resolution: verified exact; doi, observed 2026-08-15T23:50:49.646514Z

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This paper cites Shneiderman.

ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization Shneiderman

Reference 84

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ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization Understanding Neural Networks Through Deep Visualization

Reference 85

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Reference 86

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ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization Unresolved cited work

Reference 87

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Observation 4c728df0-31b8-4b74-9dfe-ab148c39a76b · outbound

This paper cites https://cs.stanford.edu/people/ karpathy/cnnembed/.

ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization https://cs.stanford.edu/people/ karpathy/cnnembed/

Reference 88

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:50:51.290498Z

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Observation 5495c48e-6c7b-43f4-a456-fff94ab0f970 · outbound

This paper cites an unresolved cited work.

ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization Unresolved cited work

Reference 91

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ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization Unresolved cited work

Reference 92

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ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization Hyper-Parameter Optimization: A Review of Algorithms and Applications

Reference 94

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Observation eeab1587-2330-4935-8f19-056f9234dba7 · outbound

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ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs)

Reference 2016

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Observation bce8818f-0e79-46fd-b9db-4724f55a07fb · outbound

This paper cites doi: 10.23915/distill.

ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization doi: 10.23915/distill

Reference 2017

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Observation b2ffdd74-6413-4634-9217-3e02d9c52d02 · outbound

This paper cites an unresolved cited work.

ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization Unresolved cited work

Reference 2021

Resolution: unresolved; raw_fallback, observed 2026-08-15T23:50:51.515936Z

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Pith citing papers