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 | 178 | 2017 |
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 | 64* | 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 | 44* | 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 | 26 | 2018 |
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 | 15 | 2021 |
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 | 12 | 2016 |
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 | 11 | 2016 |
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 | 6 | 2022 |
& Hertzmann, A.(2017, October). 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 …, 0 | 5 | |
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 | 4* | 2021 |
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 | 4 | 2018 |
What makes domain generalization hard? S Madan, L You, M Zhang, H Pfister, G Kreiman arXiv preprint arXiv:2206.07802, 2022 | 3 | 2022 |
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 | 1 | 2022 |
Benchmarking Out-of-Distribution Generalization Capabilities of DNN-based Encoding Models for the Ventral Visual Cortex S Madan, W Xiao, M Cao, H Pfister, M Livingstone, G Kreiman arXiv preprint arXiv:2406.16935, 2024 | | 2024 |
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 |
DNN-based encoding models for the visual cortex fail to generalize out of the training data distribution. S Madan, W Xiao, M Cao, H Pfister, M Livingstone, G Kreiman Computational Cognitive Neuroscience (CCN), 2024 | | 2024 |
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 |
APMTH 207: Advanced Scientific Computing Y Saatchi, V Casser, C Fosco, J Lee, S Madan | | |