Conference in Uncertainty in Artificial Intelligence

UAI

CORE rank

CORE rank (raw)

Fields of research

Artificial Intelligence

Papers indexed

3,802

1985–2025

Best Artificial Intelligence conferences

Papers per year

1985243 peak2025

Most published authors

UAI papers

3,802 records sourced from DBLP. Search titles, filter by year, sort by recency.

Year	Title	Authors
2019	Convergence Analysis of Gradient-Based Learning in Continuous Games.	Benjamin Chasnov, Lillian J. Ratliff, Eric Mazumdar, Samuel Burden
2019	Block Neural Autoregressive Flow.	Nicola De Cao, Wilker Aziz, Ivan Titov
2019	Fake It Till You Make It: Learning-Compatible Performance Support.	Jonathan Bragg, Emma Brunskill
2019	Beyond Structural Causal Models: Causal Constraints Models.	Tineke Blom, Stephan Bongers, Joris M. Mooij
2019	Identification In Missing Data Models Represented By Directed Acyclic Graphs.	Rohit Bhattacharya, Razieh Nabi, Ilya Shpitser, James M. Robins
2019	Causal Inference Under Interference And Network Uncertainty.	Rohit Bhattacharya, Daniel Malinsky, Ilya Shpitser
2019	Approximate Causal Abstractions.	Sander Beckers, Frederick Eberhardt, Joseph Y. Halpern
2019	Augmenting and Tuning Knowledge Graph Embeddings.	Robert Bamler, Farnood Salehi, Stephan Mandt
2019	Interpretable Almost Matching Exactly With Instrumental Variables.	M. Usaid Awan, Yameng Liu, Marco Morucci, Sudeepa Roy, Cynthia Rudin, Alexander Volfovsky
2019	Countdown Regression: Sharp and Calibrated Survival Predictions.	Anand Avati, Tony Duan, Sharon Zhou, Kenneth Jung, Nigam H. Shah, Andrew Y. Ng
2019	Real-Time Robotic Search using Structural Spatial Point Processes.	Olov Andersson, Per Sidn, Johan Dahlin, Patrick Doherty, Mattias Villani
2019	Adaptively Truncating Backpropagation Through Time to Control Gradient Bias.	Christopher Aicher, Nicholas J. Foti, Emily B. Fox
2019	N-GCN: Multi-scale Graph Convolution for Semi-supervised Node Classification.	Sami Abu-El-Haija, Amol Kapoor, Bryan Perozzi, Joonseok Lee
2019	BubbleRank: Safe Online Learning to Re-Rank via Implicit Click Feedback.	Chang Li, Branislav Kveton, Tor Lattimore, Ilya Markov, Maarten de Rijke, Csaba Szepesvri, Masrour Zoghi
2019	Efficient Multitask Feature and Relationship Learning.	Han Zhao, Otilia Stretcu, Alexander J. Smola, Geoffrey J. Gordon
2019	Fisher-Bures Adversary Graph Convolutional Networks.	Ke Sun, Piotr Koniusz, Zhen Wang
2019	Variational Training for Large-Scale Noisy-OR Bayesian Networks.	Geng Ji, Dehua Cheng, Huazhong Ning, Changhe Yuan, Hanning Zhou, Liang Xiong, Erik B. Sudderth
2018	Subsampled Stochastic Variance-Reduced Gradient Langevin Dynamics.	Difan Zou, Pan Xu, Quanquan Gu
2018	Clustered Fused Graphical Lasso.	Yizhi Zhu, Oluwasanmi Koyejo
2018	Stable Gradient Descent.	Yingxue Zhou, Sheng Chen, Arindam Banerjee
2018	Active Information Acquisition for Linear Optimization.	Shuran Zheng, Bo Waggoner, Yang Liu, Yiling Chen
2018	Unsupervised Learning of Latent Physical Properties Using Perception-Prediction Networks.	David Zheng, Vinson Luo, Jiajun Wu, Joshua B. Tenenbaum
2018	A Lagrangian Perspective on Latent Variable Generative Models.	Shengjia Zhao, Jiaming Song, Stefano Ermon
2018	A Cost-Effective Framework for Preference Elicitation and Aggregation.	Zhibing Zhao, Haoming Li, Junming Wang, Jeffrey O. Kephart, Nicholas Mattei, Hui Su, Lirong Xia
2018	Frank-Wolfe Optimization for Symmetric-NMF under Simplicial Constraint.	Han Zhao, Geoffrey J. Gordon

1,351–1,375 of 3,802← Previous Next →

Comparable venues

Other A*/A conferences filed under the same field of research.