Vikram V. Ramaswamy

According to our database, Vikram V. Ramaswamy authored at least 10 papers between 2021 and 2023.

Collaborative distances:

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

2023

UFO: A unified method for controlling Understandability and Faithfulness Objectives in concept-based explanations for CNNs.

Vikram V. Ramaswamy, Sunnie S. Y. Kim, Ruth Fong, Olga Russakovsky

CoRR, 2023

Beyond web-scraping: Crowd-sourcing a geographically diverse image dataset.

Vikram V. Ramaswamy, Sing Yu Lin, Dora Zhao, Aaron B. Adcock, Laurens van der Maaten, Deepti Ghadiyaram, Olga Russakovsky

CoRR, 2023

GeoDE: a Geographically Diverse Evaluation Dataset for Object Recognition.

Vikram V. Ramaswamy, Sing Yu Lin, Dora Zhao, Aaron Adcock, Laurens van der Maaten, Deepti Ghadiyaram, Olga Russakovsky

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Gender Artifacts in Visual Datasets.

Nicole Meister, Dora Zhao, Angelina Wang, Vikram V. Ramaswamy, Ruth Fong, Olga Russakovsky

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Overlooked Factors in Concept-Based Explanations: Dataset Choice, Concept Learnability, and Human Capability.

Vikram V. Ramaswamy, Sunnie S. Y. Kim, Ruth Fong, Olga Russakovsky

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

Overlooked factors in concept-based explanations: Dataset choice, concept salience, and human capability.

Vikram V. Ramaswamy, Sunnie S. Y. Kim, Ruth Fong, Olga Russakovsky

CoRR, 2022

ELUDE: Generating interpretable explanations via a decomposition into labelled and unlabelled features.

Vikram V. Ramaswamy, Sunnie S. Y. Kim, Nicole Meister, Ruth Fong, Olga Russakovsky

CoRR, 2022

Towards Intersectionality in Machine Learning: Including More Identities, Handling Underrepresentation, and Performing Evaluation.

Angelina Wang, Vikram V. Ramaswamy, Olga Russakovsky

Proceedings of the FAccT '22: 2022 ACM Conference on Fairness, Accountability, and Transparency, Seoul, Republic of Korea, June 21, 2022

HIVE: Evaluating the Human Interpretability of Visual Explanations.

Sunnie S. Y. Kim, Nicole Meister, Vikram V. Ramaswamy, Ruth Fong, Olga Russakovsky

Proceedings of the Computer Vision - ECCV 2022, 2022

2021

Fair Attribute Classification Through Latent Space De-Biasing.

Vikram V. Ramaswamy, Sunnie S. Y. Kim, Olga Russakovsky

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021