Trivedi, Puja

10 publications

ICLR 2025 A Large-Scale Training Paradigm for Graph Generative Models Yu Wang, Ryan A. Rossi, Namyong Park, Huiyuan Chen, Nesreen K. Ahmed, Puja Trivedi, Franck Dernoncourt, Danai Koutra, Tyler Derr

ICLR 2024 Accurate and Scalable Estimation of Epistemic Uncertainty for Graph Neural Networks Puja Trivedi, Mark Heimann, Rushil Anirudh, Danai Koutra, Jayaraman J. Thiagarajan

ICML 2024 Editing Partially Observable Networks via Graph Diffusion Models Puja Trivedi, Ryan A. Rossi, David Arbour, Tong Yu, Franck Dernoncourt, Sungchul Kim, Nedim Lipka, Namyong Park, Nesreen K. Ahmed, Danai Koutra

ICLR 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

ICML 2024 PAGER: Accurate Failure Characterization in Deep Regression Models Jayaraman J. Thiagarajan, Vivek Narayanaswamy, Puja Trivedi, Rushil Anirudh

ICLR 2023 A Closer Look at Model Adaptation Using Feature Distortion and Simplicity Bias Puja Trivedi, Danai Koutra, Jayaraman J. Thiagarajan

NeurIPSW 2023 Estimating Epistemic Uncertainty of Graph Neural Networks Using Stochastic Centering Puja Trivedi, Mark Heimann, Rushil Anirudh, Danai Koutra, Jayaraman J. Thiagarajan

NeurIPSW 2022 A Closer Look at Model Adaptation Using Feature Distortion and Simplicity Bias Puja Trivedi, Danai Koutra, Jayaraman J. Thiagarajan

NeurIPS 2022 Analyzing Data-Centric Properties for Graph Contrastive Learning Puja Trivedi, Ekdeep S Lubana, Mark Heimann, Danai Koutra, Jayaraman Thiagarajan

CoLLAs 2022 How Do Quadratic Regularizers Prevent Catastrophic Forgetting: The Role of Interpolation Ekdeep Singh Lubana, Puja Trivedi, Danai Koutra, Robert Dick