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03/20/2023
Polynomial Implicit Neural Representations For Large Diverse Datasets
Implicit neural representations (INR) have gained significant popularity...
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02/27/2023
Leveraging Angular Distributions for Improved Knowledge Distillation
Knowledge distillation as a broad class of methods has led to the develo...
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11/08/2022
Understanding the Role of Mixup in Knowledge Distillation: An Empirical Study
Mixup is a popular data augmentation technique based on creating new sam...
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05/24/2022
Deep Geometric Moment
Deep networks for image classification often rely more on texture inform...
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01/01/2022
Role of Data Augmentation Strategies in Knowledge Distillation for Wearable Sensor Data
Deep neural networks are parametrized by several thousands or millions o...
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05/06/2020
GraCIAS: Grassmannian of Corrupted Images for Adversarial Security
Input transformation based defense strategies fall short in defending ag...
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07/22/2019
Product of Orthogonal Spheres Parameterization for Disentangled Representation Learning
Learning representations that can disentangle explanatory attributes und...
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07/03/2019
Primate Face Identification in the Wild
Ecological imbalance owing to rapid urbanization and deforestation has a...
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02/19/2019
Geometry of Deep Generative Models for Disentangled Representations
Deep generative models like variational autoencoders approximate the int...
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11/02/2018
Unique Identification of Macaques for Population Monitoring and Control
Despite loss of natural habitat due to development and urbanization, cer...
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07/26/2018
Perturbation Robust Representations of Topological Persistence Diagrams
Topological methods for data analysis present opportunities for enforcin...
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06/05/2018
