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2020 – today
- 2024
[j1]April Chen
, Ryan A. Rossi, Namyong Park, Puja Trivedi, Yu Wang, Tong Yu, Sungchul Kim, Franck Dernoncourt, Nesreen K. Ahmed:
Fairness-Aware Graph Neural Networks: A Survey. ACM Trans. Knowl. Discov. Data 18(6): 138:1-138:23 (2024)- [c11]Puja Trivedi, Danai Koutra, Jayaraman J. Thiagarajan:
On Estimating Link Prediction Uncertainty Using Stochastic Centering. ICASSP 2024: 6810-6814 - [c10]Namyong Park, Xing Wang, Antoine Simoulin, Shuai Yang, Grey Yang, Ryan A. Rossi, Puja Trivedi, Nesreen K. Ahmed:
Forward Learning of Graph Neural Networks. ICLR 2024 - [c9]Puja Trivedi, Mark Heimann, Rushil Anirudh, Danai Koutra, Jayaraman J. Thiagarajan:
Accurate and Scalable Estimation of Epistemic Uncertainty for Graph Neural Networks. ICLR 2024 - [c8]Jayaraman J. Thiagarajan, Vivek Sivaraman Narayanaswamy, Puja Trivedi, Rushil Anirudh:
PAGER: Accurate Failure Characterization in Deep Regression Models. ICML 2024 - [c7]Puja Trivedi, Ryan A. Rossi, David Arbour, Tong Yu, Franck Dernoncourt, Sungchul Kim, Nedim Lipka, Namyong Park, Nesreen K. Ahmed, Danai Koutra:
Editing Partially Observable Networks via Graph Diffusion Models. ICML 2024 - [i15]Puja Trivedi, Mark Heimann, Rushil Anirudh, Danai Koutra, Jayaraman J. Thiagarajan:
Accurate and Scalable Estimation of Epistemic Uncertainty for Graph Neural Networks. CoRR abs/2401.03350 (2024) - [i14]Namyong Park, Xing Wang, Antoine Simoulin, Shuai Yang, Grey Yang, Ryan A. Rossi, Puja Trivedi, Nesreen K. Ahmed:
Forward Learning of Graph Neural Networks. CoRR abs/2403.11004 (2024) - [i13]Yu Wang, Ryan A. Rossi, Namyong Park, Huiyuan Chen, Nesreen K. Ahmed, Puja Trivedi, Franck Dernoncourt, Danai Koutra, Tyler Derr:
Large Generative Graph Models. CoRR abs/2406.05109 (2024) - 2023
- [c6]Puja Trivedi, Danai Koutra, Jayaraman J. Thiagarajan:
A Closer Look At Scoring Functions And Generalization Prediction. ICASSP 2023: 1-5 - [c5]Puja Trivedi, Danai Koutra, Jayaraman J. Thiagarajan:
A Closer Look at Model Adaptation using Feature Distortion and Simplicity Bias. ICLR 2023 - [i12]Puja Trivedi, Danai Koutra, Jayaraman J. Thiagarajan:
A Closer Look at Model Adaptation using Feature Distortion and Simplicity Bias. CoRR abs/2303.13500 (2023) - [i11]Puja Trivedi, Danai Koutra, Jayaraman J. Thiagarajan:
A Closer Look at Scoring Functions and Generalization Prediction. CoRR abs/2303.13589 (2023) - [i10]April Chen, Ryan A. Rossi, Namyong Park, Puja Trivedi, Yu Wang, Tong Yu, Sungchul Kim, Franck Dernoncourt, Nesreen K. Ahmed:
Fairness-Aware Graph Neural Networks: A Survey. CoRR abs/2307.03929 (2023) - [i9]Puja Trivedi, Mark Heimann, Rushil Anirudh, Danai Koutra, Jayaraman J. Thiagarajan:
Accurate and Scalable Estimation of Epistemic Uncertainty for Graph Neural Networks. CoRR abs/2309.10976 (2023) - [i8]Jayaraman J. Thiagarajan, Vivek Sivaraman Narayanaswamy, Puja Trivedi, Rushil Anirudh:
PAGER: A Framework for Failure Analysis of Deep Regression Models. CoRR abs/2309.10977 (2023) - [i7]Puja Trivedi, Ryan A. Rossi, David Arbour, Tong Yu, Franck Dernoncourt, Sungchul Kim, Nedim Lipka, Namyong Park, Nesreen K. Ahmed, Danai Koutra:
Leveraging Graph Diffusion Models for Network Refinement Tasks. CoRR abs/2311.17856 (2023) - 2022
- [c4]Fatemeh Vahedian, Ruiyu Li, Puja Trivedi, Di Jin, Danai Koutra:
Leveraging the Graph Structure of Neural Network Training Dynamics. CIKM 2022: 4545-4549 - [c3]Ekdeep Singh Lubana, Puja Trivedi, Danai Koutra, Robert P. Dick:
How do Quadratic Regularizers Prevent Catastrophic Forgetting: The Role of Interpolation. CoLLAs 2022: 819-837 - [c2]Puja Trivedi, Ekdeep Singh Lubana, Mark Heimann, Danai Koutra, Jayaraman J. Thiagarajan:
Analyzing Data-Centric Properties for Graph Contrastive Learning. NeurIPS 2022 - [c1]Puja Trivedi, Ekdeep Singh Lubana, Yujun Yan, Yaoqing Yang, Danai Koutra:
Augmentations in Graph Contrastive Learning: Current Methodological Flaws & Towards Better Practices. WWW 2022: 1538-1549 - [i6]Puja Trivedi, Danai Koutra, Jayaraman J. Thiagarajan:
Exploring the Design of Adaptation Protocols for Improved Generalization and Machine Learning Safety. CoRR abs/2207.12615 (2022) - [i5]Puja Trivedi, Ekdeep Singh Lubana, Mark Heimann, Danai Koutra, Jayaraman J. Thiagarajan:
Analyzing Data-Centric Properties for Contrastive Learning on Graphs. CoRR abs/2208.02810 (2022) - 2021
- [i4]Ekdeep Singh Lubana, Puja Trivedi, Robert P. Dick:
Rethinking Quadratic Regularizers: Explicit Movement Regularization for Continual Learning. CoRR abs/2102.02805 (2021) - [i3]Puja Trivedi, Ekdeep Singh Lubana, Yujun Yan, Yaoqing Yang, Danai Koutra:
Augmentations in Graph Contrastive Learning: Current Methodological Flaws & Towards Better Practices. CoRR abs/2111.03220 (2021) - [i2]Fatemeh Vahedian, Ruiyu Li, Puja Trivedi, Di Jin, Danai Koutra:
Convolutional Neural Network Dynamics: A Graph Perspective. CoRR abs/2111.05410 (2021) - 2020
- [i1]Ekdeep Singh Lubana, Puja Trivedi, Conrad D. Hougen, Robert P. Dick, Alfred O. Hero III:
OrthoReg: Robust Network Pruning Using Orthonormality Regularization. CoRR abs/2009.05014 (2020)
Coauthor Index
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last updated on 2024-09-04 01:20 CEST by the dblp team
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