フォロー
Spandan Madan
Spandan Madan
Harvard University, Boston Children's Hospital
確認したメール アドレス: g.harvard.edu - ホームページ
タイトル
引用先
引用先
Learning visual importance for graphic designs and data visualizations
Z Bylinskii, NW Kim, P O'Donovan, S Alsheikh, S Madan, H Pfister, ...
Proceedings of the 30th Annual ACM symposium on user interface software and …, 2017
1692017
When and how convolutional neural networks generalize to out-of-distribution category–viewpoint combinations
S Madan, T Henry, J Dozier, H Ho, N Bhandari, T Sasaki, F Durand, ...
Nature Machine Intelligence 4 (2), 146-153, 2022
48*2022
Parsing and Summarizing Infographics with Synthetically Trained Icon Detection
S Madan, Z Bylinskii, C Nobre, M Tancik, A Recasens, K Zhong, ...
2021 IEEE 14th Pacific Visualization Symposium (PacificVis), 31-40, 2021
43*2021
Synthetically trained icon proposals for parsing and summarizing infographics
S Madan, Z Bylinskii, M Tancik, A Recasens, K Zhong, S Alsheikh, ...
arXiv preprint arXiv:1807.10441, 2018
252018
When pigs fly: Contextual reasoning in synthetic and natural scenes
P Bomatter, M Zhang, D Karev, S Madan, C Tseng, G Kreiman
Proceedings of the IEEE/CVF International Conference on Computer Vision, 255-264, 2021
152021
Adversarial examples within the training distribution: A widespread challenge
S Madan, T Sasaki, H Pfister, TM Li, X Boix
arXiv preprint arXiv:2106.16198, 2023
14*2023
Exploiting the recognition code for elucidating the mechanism of zinc finger protein-DNA interactions
S Dutta, S Madan, D Sundar
BMC genomics 17, 109-125, 2016
122016
An ensemble micro neural network approach for elucidating interactions between zinc finger proteins and their target DNA
S Dutta, S Madan, H Parikh, D Sundar
Bmc Genomics 17, 97-107, 2016
112016
Three approaches to facilitate invariant neurons and generalization to out-of-distribution orientations and illuminations
A Sakai, T Sunagawa, S Madan, K Suzuki, T Katoh, H Kobashi, H Pfister, ...
Neural Networks 155, 119-143, 2022
72022
To which out-of-distribution object orientations are dnns capable of generalizing
A Cooper, X Boix, D Harari, S Madan, H Pfister, T Sasaki, P Sinha
arXiv preprint arXiv:2109.13445 4, 2021
52021
Effects of title wording on memory of trends in line graphs
A Newman, Z Bylinskii, S Haroz, S Madan, F Durand, A Oliva
Journal of Vision 18 (10), 837-837, 2018
42018
Human or Machine? Turing Tests for Vision and Language
M Zhang, G Dellaferrera, A Sikarwar, M Armendariz, N Mudrik, P Agrawal, ...
arXiv preprint arXiv:2211.13087, 2022
12022
What makes domain generalization hard?
S Madan, L You, M Zhang, H Pfister, G Kreiman
arXiv preprint arXiv:2206.07802, 2022
12022
Look Around! Unexpected gains from training on environments in the vicinity of the target
S Bono, S Madan, I Grover, M Yasueda, C Breazeal, H Pfister, G Kreiman
arXiv preprint arXiv:2401.15856, 2024
2024
Emergent Neural Network Mechanisms for Generalization to Objects in Novel Orientations
A Cooper, X Boix, D Harari, S Madan, H Pfister, T Sasaki, P Sinha
arXiv preprint arXiv:2109.13445, 2021
2021
ZoomMaps: Using Zoom to Capture Areas of Interest on Images
Z Bylinskii, A Newman, M Tancik, S Madan, F Durand, A Oliva
Journal of Vision 19 (10), 149-149, 2019
2019
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