Spandan Madan

According to our database, Spandan Madan authored at least 14 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Look Around! Unexpected gains from training on environments in the vicinity of the target.

Serena Bono, Spandan Madan, Ishaan Grover, Mao Yasueda, Cynthia Breazeal, Hanspeter Pfister, Gabriel Kreiman

CoRR, 2024

2022

Three approaches to facilitate invariant neurons and generalization to out-of-distribution orientations and illuminations.

Akira Sakai, Taro Sunagawa, Spandan Madan, Kanata Suzuki, Takashi Katoh, Hiromichi Kobashi, Hanspeter Pfister, Pawan Sinha, Xavier Boix, Tomotake Sasaki

Neural Networks, 2022

When and how convolutional neural networks generalize to out-of-distribution category-viewpoint combinations.

Spandan Madan, Timothy Henry, Jamell Dozier, Helen Ho, Nishchal Bhandari, Tomotake Sasaki, Frédo Durand, Hanspeter Pfister, Xavier Boix

Nat. Mach. Intell., 2022

Human or Machine? Turing Tests for Vision and Language.

Mengmi Zhang, Giorgia Dellaferrera, Ankur Sikarwar, Marcelo Armendáriz, Noga Mudrik, Prachi Agrawal, Spandan Madan, Andrei Barbu, Haochen Yang, Tanishq Kumar, Meghna Sadwani, Stella Dellaferrera, Michele Pizzochero, Hanspeter Pfister, Gabriel Kreiman

CoRR, 2022

What makes domain generalization hard?

Spandan Madan, Li You, Mengmi Zhang, Hanspeter Pfister, Gabriel Kreiman

CoRR, 2022

2021

Three approaches to facilitate DNN generalization to objects in out-of-distribution orientations and illuminations: late-stopping, tuning batch normalization and invariance loss.

Akira Sakai, Taro Sunagawa, Spandan Madan, Kanata Suzuki, Takashi Katoh, Hiromichi Kobashi, Hanspeter Pfister, Pawan Sinha, Xavier Boix, Tomotake Sasaki

CoRR, 2021

To Which Out-Of-Distribution Object Orientations Are DNNs Capable of Generalizing?

Avi Cooper, Xavier Boix, Daniel Harari, Spandan Madan, Hanspeter Pfister, Tomotake Sasaki, Pawan Sinha

CoRR, 2021

Small in-distribution changes in 3D perspective and lighting fool both CNNs and Transformers.

Spandan Madan, Tomotake Sasaki, Tzu-Mao Li, Xavier Boix, Hanspeter Pfister

CoRR, 2021

When Pigs Fly: Contextual Reasoning in Synthetic and Natural Scenes.

Philipp Bomatter, Mengmi Zhang, Dimitar Karev, Spandan Madan, Claire Tseng, Gabriel Kreiman

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Parsing and Summarizing Infographics with Synthetically Trained Icon Detection.

Spandan Madan, Zoya Bylinskii, Carolina Nobre, Matthew Tancik, Adrià Recasens, Kimberli Zhong, Sami Alsheikh, Aude Oliva, Frédo Durand, Hanspeter Pfister

Proceedings of the 14th IEEE Pacific Visualization Symposium, 2021

2020

On the Capability of Neural Networks to Generalize to Unseen Category-Pose Combinations.

Spandan Madan, Timothy Henry, Jamell Dozier, Helen Ho, Nishchal Bhandari, Tomotake Sasaki, Frédo Durand, Hanspeter Pfister, Xavier Boix

CoRR, 2020

2018

Synthetically Trained Icon Proposals for Parsing and Summarizing Infographics.

Spandan Madan, Zoya Bylinskii, Matthew Tancik, Adrià Recasens, Kimberli Zhong, Sami Alsheikh, Hanspeter Pfister, Aude Oliva, Frédo Durand

CoRR, 2018

2017

Understanding Infographics through Textual and Visual Tag Prediction.

Zoya Bylinskii, Sami Alsheikh, Spandan Madan, Adrià Recasens, Kimberli Zhong, Hanspeter Pfister, Frédo Durand, Aude Oliva

CoRR, 2017

Learning Visual Importance for Graphic Designs and Data Visualizations.

Zoya Bylinskii, Nam Wook Kim, Peter O'Donovan, Sami Alsheikh, Spandan Madan, Hanspeter Pfister, Frédo Durand, Bryan C. Russell, Aaron Hertzmann

Proceedings of the 30th Annual ACM Symposium on User Interface Software and Technology, 2017