Neville, Jennifer

33 publications

NeurIPS 2025 Lost in Transmission: When and Why LLMs Fail to Reason Globally Tobias Schnabel, Kiran Tomlinson, Adith Swaminathan, Jennifer Neville

ICLR 2025 Node Similarities Under Random Projections: Limits and Pathological Cases Tvrtko Tadić, Cassiano O Becker, Jennifer Neville

UAI 2024 On Overcoming Miscalibrated Conversational Priors in LLM-Based ChatBots Christine Herlihy, Jennifer Neville, Tobias Schnabel, Adith Swaminathan

NeurIPSW 2024 WildFeedback: Aligning LLMs with In-Situ User Interactions and Feedback Taiwei Shi, Zhuoer Wang, Longqi Yang, Ying-Chun Lin, Zexue He, Mengting Wan, Pei Zhou, Sujay Kumar Jauhar, Xiaofeng Xu, Xia Song, Jennifer Neville

NeurIPSW 2023 Balancing Multiple Objectives for Efficient Metaprompts for Data Labeling Tasks with Extensive Guidelines Tobias Schnabel, Jennifer Neville

ICML 2023 Hindsight Learning for MDPs with Exogenous Inputs Sean R. Sinclair, Felipe Vieira Frujeri, Ching-An Cheng, Luke Marshall, Hugo De Oliveira Barbalho, Jingling Li, Jennifer Neville, Ishai Menache, Adith Swaminathan

AAAI 2023 Thirty-Seventh AAAI Conference on Artificial Intelligence, AAAI 2023, Thirty-Fifth Conference on Innovative Applications of Artificial Intelligence, IAAI 2023, Thirteenth Symposium on Educational Advances in Artificial Intelligence, EAAI 2023, Washington, DC, USA, February 7-14, 2023 Brian Williams, Yiling Chen, Jennifer Neville

ICML 2021 A Collective Learning Framework to Boost GNN Expressiveness for Node Classification Mengyue Hang, Jennifer Neville, Bruno Ribeiro

NeurIPS 2021 Adversarial Graph Augmentation to Improve Graph Contrastive Learning Susheel Suresh, Pan Li, Cong Hao, Jennifer Neville

JMLR 2020 Ensemble Learning for Relational Data Hoda Eldardiry, Jennifer Neville, Ryan A. Rossi

AISTATS 2019 A Stein–Papangelou Goodness-of-Fit Test for Point Processes Jiasen Yang, Vinayak Rao, Jennifer Neville

IJCAI 2019 Exploiting Interaction Links for Node Classification with Deep Graph Neural Networks Hogun Park, Jennifer Neville

UAI 2019 Social Reinforcement Learning to Combat Fake News Spread Mahak Goindani, Jennifer Neville

AAAI 2019 TransConv: Relationship Embedding in Social Networks Yi-Yu Lai, Jennifer Neville, Dan Goldwasser

ICML 2018 Goodness-of-Fit Testing for Discrete Distributions via Stein Discrepancy Jiasen Yang, Qiang Liu, Vinayak Rao, Jennifer Neville

AISTATS 2018 Nested CRP with Hawkes-Gaussian Processes Xi Tan, Vinayak A. Rao, Jennifer Neville

AAAI 2018 Subgraph Pattern Neural Networks for High-Order Graph Evolution Prediction Changping Meng, S. Chandra Mouli, Bruno Ribeiro, Jennifer Neville

UAI 2018 The Indian Buffet Hawkes Process to Model Evolving Latent Influences Xi Tan, Vinayak A. Rao, Jennifer Neville

UAI 2017 Decoupling Homophily and Reciprocity with Latent Space Network Models Jiasen Yang, Vinayak A. Rao, Jennifer Neville

AAAI 2017 Deep Collective Inference John Moore, Jennifer Neville

IJCAI 2017 Unified Representation and Lifted Sampling for Generative Models of Social Networks Pablo Robles-Granda, Sebastián Moreno, Jennifer Neville

AAAI 2015 Incorporating Assortativity and Degree Dependence into Scalable Network Models Stephen Mussmann, John Moore, Joseph John Pfeiffer Iii, Jennifer Neville

JAIR 2012 Transforming Graph Data for Statistical Relational Learning Ryan A. Rossi, Luke K. McDowell, David William Aha, Jennifer Neville

AAAI 2011 Across-Model Collective Ensemble Classification Hoda Eldardiry, Jennifer Neville

ECML-PKDD 2011 Correcting Bias in Statistical Tests for Network Classifier Evaluation Tao Wang, Jennifer Neville, Brian Gallagher, Tina Eliassi-Rad

MLJ 2011 Introduction to the Special Issue on Mining and Learning with Graphs S. V. N. Vishwanathan, Samuel Kaski, Jennifer Neville, Stefan Wrobel

ICML 2011 Relational Active Learning for Joint Collective Classification Models Ankit Kuwadekar, Jennifer Neville

AISTATS 2011 Relational Learning with One Network: An Asymptotic Analysis Rongjing Xiang, Jennifer Neville

MLJ 2008 A Bias/variance Decomposition for Models Using Collective Inference Jennifer Neville, David D. Jensen

JMLR 2007 Relational Dependency Networks Jennifer Neville, David Jensen

AAAI 2005 Structure Learning for Statistical Relational Models Jennifer Neville

ICML 2003 Avoiding Bias When Aggregating Relational Data with Degree Disparity David D. Jensen, Jennifer Neville, Michael Hay

ICML 2002 Linkage and Autocorrelation Cause Feature Selection Bias in Relational Learning David D. Jensen, Jennifer Neville