Puja Trivedi

32 papers A* 9A 1Misc 2Journal 18Unranked 2
YearRankTypeTitle / Venue / Authors
2026 A* conf
GraphTextack: A Realistic Black-Box Node Injection Attack on LLM-Enhanced GNNs.
AAAI
Jiaji Ma, Puja Trivedi, Danai Koutra
2025 A* conf
A Large-scale Training Paradigm for Graph Generative Models.
ICLR
Yu Wang, Ryan A. Rossi, Namyong Park, Huiyuan Chen, Nesreen K. Ahmed, Puja Trivedi, Franck Dernoncourt, Danai Koutra, Tyler Derr
2025 — conf
Bridging the Scientific Knowledge Gap and Reproducibility: A Survey of Provenance, Assertion and Evidence Ontologies.
WWW (Companion Volume)
Tek Raj Chhetri, Yaroslav O. Halchenko, Dorota Jarecka, Puja Trivedi, Satrajit S. Ghosh, Patrick Ray, Lydia Ng
2025 J jnl
GRAPHTEXTACK: A Realistic Black-Box Node Injection Attack on LLM-Enhanced GNNs.
CoRR
Jiaji Ma, Puja Trivedi, Danai Koutra
2025 J jnl
STRUCTSENSE: A Task-Agnostic Agentic Framework for Structured Information Extraction with Human-In-The-Loop Evaluation and Benchmarking.
CoRR
Tek Raj Chhetri, Yibei Chen, Puja Trivedi, Dorota Jarecka, Saif Haobsh, Patrick Ray, Lydia Ng, Satrajit S. Ghosh
2024 A* conf
Accurate and Scalable Estimation of Epistemic Uncertainty for Graph Neural Networks.
ICLR
Puja Trivedi, Mark Heimann, Rushil Anirudh, Danai Koutra, Jayaraman J. Thiagarajan
2024 J jnl
Accurate and Scalable Estimation of Epistemic Uncertainty for Graph Neural Networks.
CoRR
Puja Trivedi, Mark Heimann, Rushil Anirudh, Danai Koutra, Jayaraman J. Thiagarajan
2024 A* conf
Editing Partially Observable Networks via Graph Diffusion Models.
ICML
Puja Trivedi, Ryan A. Rossi, David Arbour, Tong Yu, Franck Dernoncourt, Sungchul Kim, Nedim Lipka, Namyong Park, Nesreen K. Ahmed, Danai Koutra
2024 J jnl
Fairness-Aware Graph Neural Networks: A Survey.
ACM Trans. Knowl. Discov. Data
April Chen, Ryan A. Rossi, Namyong Park, Puja Trivedi, Yu Wang, Tong Yu, Sungchul Kim, Franck Dernoncourt, Nesreen K. Ahmed
2024 A* conf
Forward Learning of Graph Neural Networks.
ICLR
Namyong Park, Xing Wang, Antoine Simoulin, Shuai Yang, Grey Yang, Ryan A. Rossi, Puja Trivedi, Nesreen K. Ahmed
2024 J jnl
Forward Learning of Graph Neural Networks.
CoRR
Namyong Park, Xing Wang, Antoine Simoulin, Shuai Yang, Grey Yang, Ryan A. Rossi, Puja Trivedi, Nesreen K. Ahmed
2024 J jnl
Large Generative Graph Models.
CoRR
Yu Wang, Ryan A. Rossi, Namyong Park, Huiyuan Chen, Nesreen K. Ahmed, Puja Trivedi, Franck Dernoncourt, Danai Koutra, Tyler Derr
2024 Misc conf
On Estimating Link Prediction Uncertainty Using Stochastic Centering.
ICASSP
Puja Trivedi, Danai Koutra, Jayaraman J. Thiagarajan
2024 A* conf
PAGER: Accurate Failure Characterization in Deep Regression Models.
ICML
Jayaraman J. Thiagarajan, Vivek Sivaraman Narayanaswamy, Puja Trivedi, Rushil Anirudh
2023 Misc conf
A Closer Look At Scoring Functions And Generalization Prediction.
ICASSP
Puja Trivedi, Danai Koutra, Jayaraman J. Thiagarajan
2023 A* conf
A Closer Look at Model Adaptation using Feature Distortion and Simplicity Bias.
ICLR
Puja Trivedi, Danai Koutra, Jayaraman J. Thiagarajan
2023 J jnl
A Closer Look at Model Adaptation using Feature Distortion and Simplicity Bias.
CoRR
Puja Trivedi, Danai Koutra, Jayaraman J. Thiagarajan
2023 J jnl
A Closer Look at Scoring Functions and Generalization Prediction.
CoRR
Puja Trivedi, Danai Koutra, Jayaraman J. Thiagarajan
2023 J jnl
Accurate and Scalable Estimation of Epistemic Uncertainty for Graph Neural Networks.
CoRR
Puja Trivedi, Mark Heimann, Rushil Anirudh, Danai Koutra, Jayaraman J. Thiagarajan
2023 J jnl
Fairness-Aware Graph Neural Networks: A Survey.
CoRR
April Chen, Ryan A. Rossi, Namyong Park, Puja Trivedi, Yu Wang, Tong Yu, Sungchul Kim, Franck Dernoncourt, Nesreen K. Ahmed
2023 J jnl
Leveraging Graph Diffusion Models for Network Refinement Tasks.
CoRR
Puja Trivedi, Ryan A. Rossi, David Arbour, Tong Yu, Franck Dernoncourt, Sungchul Kim, Nedim Lipka, Namyong Park, Nesreen K. Ahmed, Danai Koutra
2023 J jnl
PAGER: A Framework for Failure Analysis of Deep Regression Models.
CoRR
Jayaraman J. Thiagarajan, Vivek Sivaraman Narayanaswamy, Puja Trivedi, Rushil Anirudh
2022 J jnl
Analyzing Data-Centric Properties for Contrastive Learning on Graphs.
CoRR
Puja Trivedi, Ekdeep Singh Lubana, Mark Heimann, Danai Koutra, Jayaraman J. Thiagarajan
2022 A* conf
Analyzing Data-Centric Properties for Graph Contrastive Learning.
NeurIPS
Puja Trivedi, Ekdeep Singh Lubana, Mark Heimann, Danai Koutra, Jayaraman J. Thiagarajan
2022 A* conf
Augmentations in Graph Contrastive Learning: Current Methodological Flaws & Towards Better Practices.
WWW
Puja Trivedi, Ekdeep Singh Lubana, Yujun Yan, Yaoqing Yang, Danai Koutra
2022 J jnl
Exploring the Design of Adaptation Protocols for Improved Generalization and Machine Learning Safety.
CoRR
Puja Trivedi, Danai Koutra, Jayaraman J. Thiagarajan
2022 — conf
How do Quadratic Regularizers Prevent Catastrophic Forgetting: The Role of Interpolation.
CoLLAs
Ekdeep Singh Lubana, Puja Trivedi, Danai Koutra, Robert P. Dick
2022 A conf
Leveraging the Graph Structure of Neural Network Training Dynamics.
CIKM
Fatemeh Vahedian, Ruiyu Li, Puja Trivedi, Di Jin, Danai Koutra
2021 J jnl
Augmentations in Graph Contrastive Learning: Current Methodological Flaws & Towards Better Practices.
CoRR
Puja Trivedi, Ekdeep Singh Lubana, Yujun Yan, Yaoqing Yang, Danai Koutra
2021 J jnl
Convolutional Neural Network Dynamics: A Graph Perspective.
CoRR
Fatemeh Vahedian, Ruiyu Li, Puja Trivedi, Di Jin, Danai Koutra
2021 J jnl
Rethinking Quadratic Regularizers: Explicit Movement Regularization for Continual Learning.
CoRR
Ekdeep Singh Lubana, Puja Trivedi, Robert P. Dick
2020 J jnl
OrthoReg: Robust Network Pruning Using Orthonormality Regularization.
CoRR
Ekdeep Singh Lubana, Puja Trivedi, Conrad D. Hougen, Robert P. Dick, Alfred O. Hero III