Xavier Boix

Publication Activity (10 Years)

Years Active: 2009-2024
Publications (10 Years): 37

Top Topics

Top Venues

AAAI Spring Symposia

Publications

Amir Rahimi, Vanessa D'Amario, Moyuru Yamada, Kentaro Takemoto, Tomotake Sasaki, Xavier Boix
D3: Data Diversity Design for Systematic Generalization in Visual Question Answering. Trans. Mach. Learn. Res. 2024 (2024)
Hojin Jang, Pawan Sinha, Xavier Boix
Configural processing as an optimized strategy for robust object recognition in neural networks. CoRR (2024)
Ece Ozkan, Xavier Boix
Multi-domain improves out-of-distribution and data-limited scenarios for medical image analysis. CoRR (2023)
Anirban Sarkar, Matthew Groth, Ian Mason, Tomotake Sasaki, Xavier Boix
Deephys: Deep Electrophysiology, Debugging Neural Networks under Distribution Shifts. CoRR (2023)
Hojin Jang, Syed Suleman Abbas Zaidi, Xavier Boix, Neeraj Prasad, Sharon Gilad-Gutnick, Shlomit Ben-Ami, Pawan Sinha
Robustness to Transformations Across Categories: Is Robustness Driven by Invariant Neural Representations? Neural Comput. 35 (12) (2023)
Amir Rahimi, Vanessa D'Amario, Moyuru Yamada, Kentaro Takemoto, Tomotake Sasaki, Xavier Boix
D3: Data Diversity Design for Systematic Generalization in Visual Question Answering. CoRR (2023)
Ian Mason, Anirban Sarkar, Tomotake Sasaki, Xavier Boix
Modularity Trumps Invariance for Compositional Robustness. CoRR (2023)
Spandan Madan, Timothy Henry, Jamell Dozier, Helen Ho, Nishchal Bhandari, Tomotake Sasaki, Frédo Durand, Hanspeter Pfister, Xavier Boix
When and how convolutional neural networks generalize to out-of-distribution category-viewpoint combinations. Nat. Mach. Intell. 4 (2) (2022)
Akira Sakai, Taro Sunagawa, Spandan Madan, Kanata Suzuki, Takashi Katoh, Hiromichi Kobashi, Hanspeter Pfister, Pawan Sinha, Xavier Boix, Tomotake Sasaki
Three approaches to facilitate invariant neurons and generalization to out-of-distribution orientations and illuminations. Neural Networks 155 (2022)
Vanessa D'Amario, Sanjana Srivastava, Tomotake Sasaki, Xavier Boix
The Data Efficiency of Deep Learning Is Degraded by Unnecessary Input Dimensions. Frontiers Comput. Neurosci. 16 (2022)
Moyuru Yamada, Vanessa D'Amario, Kentaro Takemoto, Xavier Boix, Tomotake Sasaki
Transformer Module Networks for Systematic Generalization in Visual Question Answering. CoRR (2022)
Kimberly Villalobos, Vilim Stih, Amineh Ahmadinejad, Shobhita Sundaram, Jamell Dozier, Andrew Francl, Frederico Azevedo, Tomotake Sasaki, Xavier Boix
Do Neural Networks for Segmentation Understand Insideness? CoRR (2022)
Dimitris Bertsimas, Xavier Boix, Kimberly Villalobos Carballo, Dick den Hertog
A Robust Optimization Approach to Deep Learning. CoRR (2021)
Avi Cooper, Xavier Boix, Daniel Harari, Spandan Madan, Hanspeter Pfister, Tomotake Sasaki, Pawan Sinha
To Which Out-Of-Distribution Object Orientations Are DNNs Capable of Generalizing? CoRR (2021)
Spandan Madan, Tomotake Sasaki, Tzu-Mao Li, Xavier Boix, Hanspeter Pfister
Small in-distribution changes in 3D perspective and lighting fool both CNNs and Transformers. CoRR (2021)
Vanessa D'Amario, Tomotake Sasaki, Xavier Boix
How Modular should Neural Module Networks Be for Systematic Generalization? NeurIPS (2021)
Shobhita Sundaram, Darius Sinha, Matthew Groth, Tomotake Sasaki, Xavier Boix
Symmetry Perception by Deep Networks: Inadequacy of Feed-Forward Architectures and Improvements with Recurrent Connections. CoRR (2021)
Stephen Casper, Xavier Boix, Vanessa D'Amario, Ling Guo, Martin Schrimpf, Kasper Vinken, Gabriel Kreiman
Frivolous Units: Wider Networks Are Not Really That Wide. AAAI (2021)
Kimberly Villalobos, Vilim Stih, Amineh Ahmadinejad, Shobhita Sundaram, Jamell Dozier, Andrew Francl, Frederico Azevedo, Tomotake Sasaki, Xavier Boix
Do Neural Networks for Segmentation Understand Insideness? Neural Comput. 33 (9) (2021)
Vanessa D'Amario, Tomotake Sasaki, Xavier Boix
How Modular Should Neural Module Networks Be for Systematic Generalization? CoRR (2021)
Akira Sakai, Taro Sunagawa, Spandan Madan, Kanata Suzuki, Takashi Katoh, Hiromichi Kobashi, Hanspeter Pfister, Pawan Sinha, Xavier Boix, Tomotake Sasaki
Three approaches to facilitate DNN generalization to objects in out-of-distribution orientations and illuminations: late-stopping, tuning batch normalization and invariance loss. CoRR (2021)
Vanessa D'Amario, Sanjana Srivastava, Tomotake Sasaki, Xavier Boix
The Foes of Neural Network's Data Efficiency Among Unnecessary Input Dimensions. CoRR (2021)
Syed Suleman Abbas Zaidi, Xavier Boix, Neeraj Prasad, Sharon Gilad-Gutnick, Shlomit Ben-Ami, Pawan Sinha
Is Robustness To Transformations Driven by Invariant Neural Representations? CoRR (2020)
Spandan Madan, Timothy Henry, Jamell Dozier, Helen Ho, Nishchal Bhandari, Tomotake Sasaki, Frédo Durand, Hanspeter Pfister, Xavier Boix
On the Capability of Neural Networks to Generalize to Unseen Category-Pose Combinations. CoRR (2020)
Sanjana Srivastava, Guy Ben-Yosef, Xavier Boix
Minimal Images in Deep Neural Networks: Fragile Object Recognition in Natural Images. CoRR (2019)
Stephen Casper, Xavier Boix, Vanessa D'Amario, Ling Guo, Martin Schrimpf, Kasper Vinken, Gabriel Kreiman
Removable and/or Repeated Units Emerge in Overparametrized Deep Neural Networks. CoRR (2019)
Sanjana Srivastava, Guy Ben-Yosef, Xavier Boix
Minimal Images in Deep Neural Networks: Fragile Object Recognition in Natural Images. ICLR (Poster) (2019)
Tomaso A. Poggio, Qianli Liao, Brando Miranda, Andrzej Banburski, Xavier Boix, Jack Hidary
Theory IIIb: Generalization in Deep Networks. CoRR (2018)
Tomaso A. Poggio, Kenji Kawaguchi, Qianli Liao, Brando Miranda, Lorenzo Rosasco, Xavier Boix, Jack Hidary, Hrushikesh N. Mhaskar
Theory of Deep Learning III: explaining the non-overfitting puzzle. CoRR (2018)
Ana Garcia del Molino, Xavier Boix, Joo-Hwee Lim, Ah-Hwee Tan
On Active Video Summarization: Customized Summaries via On-Line Interaction with the User. AAAI Spring Symposia (2017)
Francis X. Chen, Gemma Roig, Leyla Isik, Xavier Boix, Tomaso A. Poggio
Eccentricity Dependent Deep Neural Networks: Modeling Invariance in Human Vision. AAAI Spring Symposia (2017)
Ana Garcia del Molino, Xavier Boix, Joo-Hwee Lim, Ah-Hwee Tan
Active Video Summarization: Customized Summaries via On-line Interaction with the User. AAAI (2017)
Anna Volokitin, Michael Gygli, Xavier Boix
Predicting When Eye Fixations Are Consistent. AAAI Spring Symposia (2017)
Jeannette Bohg, Xavier Boix, Nancy Chang, Elizabeth F. Churchill, Vivian Chu, Fei Fang, Jerome Feldman, Avelino J. Gonzalez, Takashi Kido, William F. Lawless, José L. Montaña, Santiago Ontañón, Jivko Sinapov, Donald A. Sofge, Luc Steels, Molly Wright Steenson, Keiki Takadama, Amulya Yadav
Reports on the 2017 AAAI Spring Symposium Series. AI Mag. 38 (4) (2017)
Ece Ozkan, Gemma Roig, Orcun Goksel, Xavier Boix
Herding Generalizes Diverse M -Best Solutions. CoRR (2016)
Ming Jiang, Xavier Boix, Gemma Roig, Juan Xu, Luc Van Gool, Qi Zhao
Learning to Predict Sequences of Human Visual Fixations. IEEE Trans. Neural Networks Learn. Syst. 27 (6) (2016)
Anna Volokitin, Michael Gygli, Xavier Boix
Predicting When Saliency Maps are Accurate and Eye Fixations Consistent. CVPR (2016)
Xun Huang, Chengyao Shen, Xavier Boix, Qi Zhao
SALICON: Reducing the Semantic Gap in Saliency Prediction by Adapting Deep Neural Networks. ICCV (2015)
Michael Van den Bergh, Xavier Boix, Gemma Roig, Luc Van Gool
SEEDS: Superpixels Extracted Via Energy-Driven Sampling. Int. J. Comput. Vis. 111 (3) (2015)
Ming Jiang, Xavier Boix, Juan Xu, Gemma Roig, Luc Van Gool, Qi Zhao
Saliency Prediction with Active Semantic Segmentation. BMVC (2015)
Yan Luo, Xavier Boix, Gemma Roig, Tomaso A. Poggio, Qi Zhao
Foveation-based Mechanisms Alleviate Adversarial Examples. CoRR (2015)
Xavier Boix, Gemma Roig, Luc Van Gool
Comment on "Ensemble Projection for Semi-supervised Image Classification". CoRR (2014)
Alex Locher, Lennart Elsen, Xavier Boix, Luc Van Gool
Reconstruction of Inextensible Surfaces on a Budget via Bootstrapping. 3DV (2014)
Xavier Boix, Gemma Roig, Salomon Diether, Luc Van Gool
Self-Adaptable Templates for Feature Coding. NIPS (2014)
Michael Van den Bergh, Xavier Boix, Gemma Roig, Luc Van Gool
SEEDS: Superpixels Extracted via Energy-Driven Sampling. CoRR (2013)
Michael Van den Bergh, Gemma Roig, Xavier Boix, Santiago Manen, Luc Van Gool
Online Video SEEDS for Temporal Window Objectness. ICCV (2013)
Gemma Roig, Xavier Boix, Roderick de Nijs, Sebastian Ramos, Kolja Kühnlenz, Luc Van Gool
Active MAP Inference in CRFs for Efficient Semantic Segmentation. ICCV (2013)
Gemma Roig, Xavier Boix, Luc Van Gool
Random Binary Mappings for Kernel Learning and Efficient SVM. CoRR (2013)
Xavier Boix, Michael Gygli, Gemma Roig, Luc Van Gool
Sparse Quantization for Patch Description. CVPR (2013)
Xavier Boix, Josep M. Gonfaus, Joost van de Weijer, Andrew D. Bagdanov, Joan Serrat Gual, Jordi Gonzàlez
Harmony Potentials - Fusing Global and Local Scale for Semantic Image Segmentation. Int. J. Comput. Vis. 96 (1) (2012)
Xavier Boix, Gemma Roig, Christian Leistner, Luc Van Gool
Nested Sparse Quantization for Efficient Feature Coding. ECCV (2) (2012)
Michael Van den Bergh, Xavier Boix, Gemma Roig, Benjamin de Capitani, Luc Van Gool
SEEDS: Superpixels Extracted via Energy-Driven Sampling. ECCV (7) (2012)
Roderick de Nijs, Sebastian Ramos, Gemma Roig, Xavier Boix, Luc Van Gool, Kolja Kühnlenz
On-line semantic perception using uncertainty. IROS (2012)
Gemma Roig, Xavier Boix, Horesh Ben Shitrit, Pascal Fua
Conditional Random Fields for multi-camera object detection. ICCV (2011)
Gemma Roig, Xavier Boix, Fernando De la Torre
Optimal feature selection for subspace image matching. ICCV Workshops (2009)