Publications

For a complete publication list, visit my Google Scholar page.

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International Conference on Learning Representations (ICLR 2023)

Explaining RL Decisions with Trajectories

S. V. Deshmukh, A. Dasgupta, N. Jiang, B. Krishnamurthy, C. Agarwal, J. Subramanian, and G. Theocharous

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International Conference on Learning Representations (ICLR 2023)

GNNDelete: A General Unlearning Strategy for Graph Neural Networks

J. Cheng, G. Dasoulas, H, He, C. Agarwal, and M. Zitnik

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Nature Scientific Data (2023)

Evaluating explainability for graph neural networks

C. Agarwal, O. Queen, H. Lakkaraju, and M. Zitnik

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The First Learning on Graphs Conference(LOG 2022)

Towards Training GNNs using Explanation Directed Message Passing

V. Giunchiglia, C.V. Shukla, G. Gonzalez, and C. Agarwal

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Conference on Neural Information Processing Systems (NeurIPS 2022)

OpenXAI: Towards a Transparent Evaluation of Model Explanations

C. Agarwal, S. Krishna, E. Saxena, M. Pawelczyk, N. Johnson, I. Puri, M. Zitnik, and H. Lakkaraju

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Conference on Computer Vision and Pattern Recognition (CVPR 2022)

Estimating Example Difficulty using Variance of Gradients

C. Agarwal, D. D’souza, & S. Hooker

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International Conference on Artificial Intelligence and Statistics (AISTATS 2022)

Probing GNN Explainers: A Rigorous Theoretical and Empirical Analysis of GNN Explanation Methods

C. Agarwal, M. Zitnik, & H. Lakkaraju

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International Conference on Artificial Intelligence and Statistics (AISTATS 2022)

Exploring Counterfactual Explanations Through the Lens of Adversarial Examples: A Theoretical and Empirical Analysis

M. Pawelczyk, C. Agarwal, S. Joshi, S. Upadhyay and H. Lakkaraju

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Conference on Uncertainty in Artificial Intelligence (UAI 2021)

Towards a Unified Framework for Fair and Stable Graph Representation Learning

C. Agarwal, H.Lakkaraju, & M. Zitnik

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International Conference on Machine Learning (ICML 2021)

Towards the unification and robustness of perturbation and gradient based explanations

S. Agarwal, S. Jabbari, C. Agarwal, S. Upadhyay, Z.S. Wu, & H. Lakkaraju

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Asian Conference on Computer Vision (ACCV 2020)

Explaining image classifiers by removing input features using generative models

C. Agarwal & A. Nguyen

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WHI workshop, International Conference on Machine Learning (ICML 2020 workshop) - Spotlight presentation

Intriguing generalization and simplicity of adversarially trained neural networks

C. Agarwal*, P. Chen* & A. Nguyen

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Computer Vision and Pattern Recognition (CVPR 2020) - Oral Presentation (~5%)

SAM: The sensitivity of attribution methods to hyperparameters

N. Bansal*, C. Agarwal* & A. Nguyen*

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SPIE Medical Imaging (SPIE 2020)

CoroNet: A Deep Network Architecture for Semi-Supervised Task-Based Identification of COVID-19 from Chest X-ray Images

C. Agarwal*, S. Khobahi*, D. Schonfeld & M.Soltanalian

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IEEE Conference on Image Processing (ICIP 2019) - Spotlight (Top 10%)

Improving Adversarial Robustness by Encouraging Discriminative Features

C. Agarwal, A. Nguyen & D. Schonfeld