Deepak Vijaykeerthy

Verifying Individual Fairness in Machine Learning Models pdf

Diptikalyan Saha, Philips George John, Deepak Vijaykeerthy, 2020, UAI.

Exploring the Hyperparameter Landscape of Adversarial Robustness pdf

Ganesh Venkataraman, Evelyn Duesterwald, Mathieu Sinn, 2019, ArXiv.

Efficient synthesis of probabilistic programs

Sriram K. Rajamani, Sherjil Ozair, Aditya V. Nori, 2015, PLDI.

An ADMM Based Framework for AutoML Pipeline Configuration

Parikshit Ram, Djallel Bouneffouf, Horst Samulowitz, 2020, AAAI.

Explaining Deep Learning Models using Causal Inference pdf

Senthil Mani, Anush Sankaran, Deepak Vijaykeerthy, 2018, ArXiv.

Debugging Machine Learning Tasks pdf

Sriram K. Rajamani, Aditya V. Nori, Shayak Sen, 2016, ArXiv.

Hardening Deep Neural Networks via Adversarial Model Cascades

Sameep Mehta, Ponnurangam Kumaraguru, Anshuman Suri, 2018, 2019 International Joint Conference on Neural Networks (IJCNN).

An Introduction to Adversarial Machine Learning

Sameep Mehta, Atul Kumar, Deepak Vijaykeerthy, 2017, BDA.

Automated Testing of AI Models pdf

Diptikalyan Saha, Deepak Vijaykeerthy, Swagatam Haldar, 2021, ArXiv.

Inducing Semantic Grouping of Latent Concepts for Explanations: An Ante-Hoc Approach pdf

Vineeth N Balasubramanian, Deepak Vijaykeerthy, Anirban Sarkar, 2021, ArXiv.

A Framework for Learning Ante-hoc Explainable Models via Concepts

Vineeth N Balasubramanian, Deepak Vijaykeerthy, Anirban Sarkar, 2021, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).