Puja Trivedi

According to our database, Puja Trivedi authored at least 16 papers between 2020 and 2024.

Collaborative distances:

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

2024

Forward Learning of Graph Neural Networks.

Namyong Park, Xing Wang, Antoine Simoulin, Shuai Yang, Grey Yang, Ryan A. Rossi, Puja Trivedi, Nesreen K. Ahmed

CoRR, 2024

2023

Leveraging Graph Diffusion Models for Network Refinement Tasks.

Puja Trivedi, Ryan A. Rossi, David Arbour, Tong Yu, Franck Dernoncourt, Sungchul Kim, Nedim Lipka, Namyong Park, Nesreen K. Ahmed, Danai Koutra

CoRR, 2023

PAGER: A Framework for Failure Analysis of Deep Regression Models.

Jayaraman J. Thiagarajan, Vivek Sivaraman Narayanaswamy, Puja Trivedi, Rushil Anirudh

CoRR, 2023

Accurate and Scalable Estimation of Epistemic Uncertainty for Graph Neural Networks.

Puja Trivedi, Mark Heimann, Rushil Anirudh, Danai Koutra, Jayaraman J. Thiagarajan

CoRR, 2023

Fairness-Aware Graph Neural Networks: A Survey.

April Chen, Ryan A. Rossi, Namyong Park, Puja Trivedi, Yu Wang, Tong Yu, Sungchul Kim, Franck Dernoncourt, Nesreen K. Ahmed

CoRR, 2023

A Closer Look at Model Adaptation using Feature Distortion and Simplicity Bias.

Puja Trivedi, Danai Koutra, Jayaraman J. Thiagarajan

Proceedings of the Eleventh International Conference on Learning Representations, 2023

A Closer Look At Scoring Functions And Generalization Prediction.

Puja Trivedi, Danai Koutra, Jayaraman J. Thiagarajan

Proceedings of the IEEE International Conference on Acoustics, 2023

2022

Analyzing Data-Centric Properties for Contrastive Learning on Graphs.

Puja Trivedi, Ekdeep Singh Lubana, Mark Heimann, Danai Koutra, Jayaraman J. Thiagarajan

CoRR, 2022

Exploring the Design of Adaptation Protocols for Improved Generalization and Machine Learning Safety.

Puja Trivedi, Danai Koutra, Jayaraman J. Thiagarajan

CoRR, 2022

Augmentations in Graph Contrastive Learning: Current Methodological Flaws & Towards Better Practices.

Puja Trivedi, Ekdeep Singh Lubana, Yujun Yan, Yaoqing Yang, Danai Koutra

Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

Analyzing Data-Centric Properties for Graph Contrastive Learning.

Puja Trivedi, Ekdeep Singh Lubana, Mark Heimann, Danai Koutra, Jayaraman J. Thiagarajan

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

How do Quadratic Regularizers Prevent Catastrophic Forgetting: The Role of Interpolation.

Ekdeep Singh Lubana, Puja Trivedi, Danai Koutra, Robert P. Dick

Proceedings of the Conference on Lifelong Learning Agents, 2022

Leveraging the Graph Structure of Neural Network Training Dynamics.

Fatemeh Vahedian, Ruiyu Li, Puja Trivedi, Di Jin, Danai Koutra

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

2021

Convolutional Neural Network Dynamics: A Graph Perspective.

Fatemeh Vahedian, Ruiyu Li, Puja Trivedi, Di Jin, Danai Koutra

CoRR, 2021

Rethinking Quadratic Regularizers: Explicit Movement Regularization for Continual Learning.

Ekdeep Singh Lubana, Puja Trivedi, Robert P. Dick

CoRR, 2021

2020

OrthoReg: Robust Network Pruning Using Orthonormality Regularization.

Ekdeep Singh Lubana, Puja Trivedi, Conrad D. Hougen, Robert P. Dick, Alfred O. Hero III

CoRR, 2020