UAI 2021 Accepted Papers

The full list of 205 papers accepted at UAI 2021 (Conference on Uncertainty in Artificial Intelligence). Click any title for details, similar papers, and links to the original source. You can also search these papers by meaning, not just keywords.

1. ReZero is all you need: fast convergence at large depthPoster366 citations
2. Towards a unified framework for fair and stable graph representation learningPoster237 citations
3. High-dimensional Bayesian optimization with sparse axis-aligned subspacesPoster201 citations
4. BayLIME: Bayesian local interpretable model-agnostic explanationsPoster134 citations
5. The promises and pitfalls of deep kernel learningPoster130 citations
6. Scaling Hamiltonian Monte Carlo inference for Bayesian neural networks with symmetric splittingPoster111 citations
7. Distribution-free uncertainty quantification for classification under label shiftPoster109 citations
8. TreeBERT: A tree-based pre-trained model for programming languagePoster99 citations
9. The curious case of adversarially robust models: More data can help, double descend, or hurt generalizationPoster92 citations
10. Local explanations via necessity and sufficiency: unifying theory and practicePoster91 citations
11. The complexity of nonconvex-strongly-concave minimax optimizationPoster85 citations
12. Natural language adversarial defense through synonym encodingPoster76 citations
13. Sketching curvature for efficient out-of-distribution detection for deep neural networksPoster71 citations
14. Trumpets: Injective flows for inference and inverse problemsPoster69 citations
15. Measuring data leakage in machine-learning models with Fisher informationPoster68 citations
16. Neural markov logic networksPoster67 citations
17. Task similarity aware meta learning: theory-inspired improvement on MAMLPoster66 citations
18. Faster Convergence of Stochastic Gradient Langevin Dynamics for Non-Log-Concave SamplingPoster54 citations
19. Most: multi-source domain adaptation via optimal transport for student-teacher learningPoster54 citations
20. A decentralized policy gradient approach to multi-task reinforcement learningPoster51 citations
21. Formal verification of neural networks for safety-critical tasks in deep reinforcement learningPoster50 citations
22. Learnable uncertainty under Laplace approximationsPoster48 citations
23. Exploring the loss landscape in neural architecture searchPoster46 citations
24. Improved generalization bounds of group invariant / equivariant deep networks via quotient feature spacesPoster46 citations
25. Tensor-train density estimationPoster46 citations
26. Variational refinement for importance sampling using the forward Kullback-Leibler divergencePoster44 citations
27. Contrastive prototype learning with augmented embeddings for few-shot learningPoster43 citations
28. Invariant representation learning for treatment effect estimationPoster43 citations
29. A Nonmyopic Approach to Cost-Constrained Bayesian OptimizationPoster36 citations
30. Compositional abstraction error and a category of causal modelsPoster36 citations
31. Diagnostics for conditional density models and Bayesian inference algorithmsPoster36 citations
32. Addressing fairness in classification with a model-agnostic multi-objective algorithmPoster35 citations
33. Bandits with partially observable confounded dataPoster34 citations
34. Classification with abstention but without disparitiesPoster34 citations
35. Know your limits: Uncertainty estimation with ReLU classifiers fails at reliable OOD detectionPoster34 citations
36. Featurized density ratio estimationPoster33 citations
37. Investigating vulnerabilities of deep neural policiesPoster33 citations
38. Federated stochastic gradient Langevin dynamicsPoster30 citations
39. Hierarchical Indian buffet neural networks for Bayesian continual learningPoster30 citations
40. Causal additive models with unobserved variablesPoster29 citations
41. Contingency-aware influence maximization: A reinforcement learning approachPoster29 citations
42. Class balancing GAN with a classifier in the loopPoster28 citations
43. Optimized auxiliary particle filters: adapting mixture proposals via convex optimizationPoster28 citations
44. Combinatorial semi-bandit in the non-stationary environmentPoster27 citations
45. Constrained labeling for weakly supervised learningPoster27 citations
46. Minimax sample complexity for turn-based stochastic gamePoster27 citations
47. Bayesian streaming sparse Tucker decompositionPoster26 citations
48. Robust reinforcement learning under minimax regret for green securityPoster26 citations
49. Statistically robust neural network classificationPoster26 citations
50. Probabilistic selection of inducing points in sparse Gaussian processesPoster25 citations
51. A weaker faithfulness assumption based on triple interactionsPoster24 citations
52. variational combinatorial sequential monte carlo methods for bayesian phylogenetic inferencePoster24 citations
53. Variational inference with continuously-indexed normalizing flowsPoster23 citations
54. An optimization and generalization analysis for max-pooling networksPoster22 citations
55. Competitive policy optimizationPoster22 citations
56. Multi-task and meta-learning with sparse linear banditsPoster22 citations
57. Faster lifting for two-variable logic using cell graphsPoster21 citations
58. Generating adversarial examples with graph neural networksPoster21 citations
59. Sparse linear networks with a fixed butterfly structure: theory and practicePoster21 citations
60. Possibilistic preference elicitation by minimax regretPoster20 citations
61. Random probabilistic circuitsPoster20 citations
62. q-Paths: Generalizing the geometric annealing path using power meansPoster20 citations
63. A unifying framework for observer-aware planning and its complexityPoster19 citations
64. Incorporating causal graphical prior knowledge into predictive modeling via simple data augmentationPoster19 citations
65. Information theoretic meta learning with Gaussian processesPoster19 citations
66. Unbiased gradient estimation for variational auto-encoders using coupled Markov chainsPoster19 citations
67. Generalization error bounds for deep unfolding RNNsPoster18 citations
68. Tighter Generalization Bounds for Iterative Differentially Private Learning AlgorithmsPoster18 citations
69. Escaping from zero gradient: Revisiting action-constrained reinforcement learning via Frank-Wolfe policy optimizationPoster17 citations
70. Gaussian process nowcasting: application to COVID-19 mortality reportingPoster17 citations
71. Improving uncertainty calibration of deep neural networks via truth discovery and geometric optimizationPoster17 citations
72. On the effects of quantisation on model uncertainty in Bayesian neural networksPoster17 citations
73. Unsupervised constrained community detection via self-expressive graph neural networkPoster17 citations
74. Certification of iterative predictions in Bayesian neural networksPoster16 citations
75. Estimating treatment effects with observed confounders and mediatorsPoster16 citations
76. Identifying untrustworthy predictions in neural networks by geometric gradient analysisPoster16 citations
77. Learning and certification under instance-targeted poisoningPoster16 citations
78. Leveraging probabilistic circuits for nonparametric multi-output regressionPoster16 citations
79. Towards tractable optimism in model-based reinforcement learningPoster16 citations
80. Unsupervised anomaly detection with adversarial mirrored autoencodersPoster16 citations
81. Weighted model counting with conditional weights for Bayesian networksPoster16 citations
82. Matrix games with bandit feedbackPoster14 citations
83. Variance-dependent best arm identificationPoster14 citations
84. Communication efficient parallel reinforcement learningPoster13 citations
85. Global explanations with decision rules: a co-learning approachPoster13 citations
86. Learning proposals for probabilistic programs with inference combinatorsPoster13 citations
87. Lifted reasoning meets weighted model integrationPoster13 citations
88. Stochastic continuous normalizing flows: training SDEs as ODEsPoster13 citations
89. Confidence in causal discovery with linear causal modelsPoster12 citations
90. Improving approximate optimal transport distances using quantizationPoster12 citations
91. Mixed variable Bayesian optimization with frequency modulated kernelsPoster12 citations
92. Post-hoc loss-calibration for Bayesian neural networksPoster12 citations
93. Regstar: efficient strategy synthesis for adversarial patrolling gamesPoster12 citations
94. Trusted-maximizers entropy search for efficient Bayesian optimizationPoster12 citations
95. Asynchronous $ε$-Greedy Bayesian OptimisationPoster11 citations
96. Combining pseudo-point and state space approximations for sum-separable Gaussian ProcessesPoster11 citations
97. Decentralized multi-agent active search for sparse signalsPoster11 citations
98. Deep kernels with probabilistic embeddings for small-data learningPoster11 citations
99. Finite-time theory for momentum Q-learningPoster11 citations
100. Maximal ancestral graph structure learning via exact searchPoster11 citations
101. PROVIDE: a probabilistic framework for unsupervised video decompositionPoster11 citations
102. Active multi-fidelity Bayesian online changepoint detectionPoster10 citations
103. CLAIM: curriculum learning policy for influence maximization in unknown social networksPoster10 citations
104. Contextual policy transfer in reinforcement learning domains via deep mixtures-of-expertsPoster10 citations
105. FlexAE: flexibly learning latent priors for wasserstein auto-encodersPoster10 citations
106. Generative Archimedean copulasPoster10 citations
107. Markov equivalence of max-linear Bayesian networksPoster10 citations
108. SGD with low-dimensional gradients with applications to private and distributed learningPoster10 citations
109. Subseasonal climate prediction in the western US using Bayesian spatial modelsPoster10 citations
110. Tractable computation of expected kernelsPoster10 citations
111. Bias-corrected peaks-over-threshold estimation of the CVaRPoster9 citations
112. Enabling long-range exploration in minimization of multimodal functionsPoster9 citations
113. Explicit pairwise factorized graph neural network for semi-supervised node classificationPoster9 citations
114. Extendability of causal graphical models: Algorithms and computational complexityPoster9 citations
115. Hierarchical infinite relational modelPoster9 citations
116. LocalNewton: Reducing communication rounds for distributed learningPoster9 citations
117. Partial Identifiability in Discrete Data with Measurement ErrorPoster9 citations
118. The neural moving average model for scalable variational inference of state space modelsPoster9 citations
119. A Bayesian nonparametric conditional two-sample test with an application to Local Causal DiscoveryPoster8 citations
120. Action redundancy in reinforcement learningPoster8 citations
121. Constrained differentially private federated learning for low-bandwidth devicesPoster8 citations
122. Multi-output Gaussian Processes for uncertainty-aware recommender systemsPoster8 citations
123. On random kernels of residual architecturesPoster8 citations
124. PLSO: A generative framework for decomposing nonstationary time-series into piecewise stationary oscillatory componentsPoster8 citations
125. Thompson sampling for Markov games with piecewise stationary opponent policiesPoster8 citations
126. Bayesian optimization for modular black-box systems with switching costsPoster7 citations
127. Correlated weights in infinite limits of deep convolutional neural networksPoster7 citations
128. Disentangling mixtures of unknown causal interventionsPoster7 citations
129. Entropic Inequality Constraints from e-separation Relations in Directed Acyclic Graphs with Hidden VariablesPoster7 citations
130. Integer programming-based error-correcting output code design for robust classificationPoster7 citations
131. Min/max stability and box distributionsPoster7 citations
132. No-regret approximate inference via Bayesian optimisationPoster7 citations
133. Path dependent structural equation modelsPoster7 citations
134. RISAN: Robust instance specific deep abstention networkPoster7 citations
135. Testification of Condorcet Winners in dueling banditsPoster7 citations
136. Uncertainty in minimum cost multicuts for image and motion segmentationPoster7 citations
137. A kernel two-sample test with selection biasPoster6 citations
138. Doubly non-central beta matrix factorization for DNA methylation dataPoster6 citations
139. Efficient debiased evidence estimation by multilevel Monte Carlo samplingPoster6 citations
140. Explaining fast improvement in online imitation learningPoster6 citations
141. Graph reparameterizations for enabling 1000+ Monte Carlo iterations in Bayesian deep neural networksPoster6 citations
142. Nearest neighbor search under uncertaintyPoster6 citations
143. Principal component analysis in the stochastic differential privacy modelPoster6 citations
144. Similarity measure for sparse time course data based on Gaussian processesPoster6 citations
145. Staying in shape: learning invariant shape representations using contrastive learningPoster6 citations
146. Strategically efficient exploration in competitive multi-agent reinforcement learningPoster6 citations
147. Sum-product laws and efficient algorithms for imprecise Markov chainsPoster6 citations
148. pRSL: Interpretable multi-label stacking by learning probabilistic rulesPoster6 citations
149. Approximation algorithm for submodular maximization under submodular coverPoster5 citations
150. Conditionally independent data generationPoster5 citations
151. Convergence behavior of belief propagation: estimating regions of attraction via Lyapunov functionsPoster5 citations
152. Efficient online inference for nonparametric mixture modelsPoster5 citations
153. Exact and approximate hierarchical clustering using A*Poster5 citations
154. GP-ConvCNP: Better generalization for conditional convolutional Neural Processes on time series dataPoster5 citations
155. Known unknowns: Learning novel concepts using reasoning-by-eliminationPoster5 citations
156. On the distribution of penultimate activations of classification networksPoster5 citations
157. Simple combinatorial algorithms for combinatorial bandits: corruptions and approximationsPoster5 citations
158. A variational approximation for analyzing the dynamics of panel dataPoster4 citations
159. An unsupervised video game playstyle metric via state discretizationPoster4 citations
160. Condition number bounds for causal inferencePoster4 citations
161. Modeling financial uncertainty with multivariate temporal entropy-based curriculumsPoster4 citations
162. No-regret learning with high-probability in adversarial Markov decision processesPoster4 citations
163. SDM-Net: A simple and effective model for generalized zero-shot learningPoster4 citations
164. Towards robust episodic meta-learningPoster4 citations
165. Uncertainty-aware sensitivity analysis using Rényi divergencesPoster4 citations
166. Approximate implication with d-separationPoster3 citations
167. Causal and interventional Markov boundariesPoster3 citations
168. Defending SVMs against poisoning attacks: the hardness and DBSCAN approachPoster3 citations
169. Dynamic visualization for L1 fusion convex clustering in near-linear timePoster3 citations
170. Efficient greedy coordinate descent via variable partitioningPoster3 citations
171. Hierarchical probabilistic model for blind source separation via Legendre transformationPoster3 citations
172. Learning probabilistic sentential decision diagrams under logic constraints by sampling and averagingPoster3 citations
173. Learning to learn with Gaussian processesPoster3 citations
174. NP-DRAW: A Non-Parametric Structured Latent Variable Model for Image GenerationPoster3 citations
175. Probabilistic DAG searchPoster3 citations
176. Symmetric Wasserstein autoencodersPoster3 citations
177. Unsupervised program synthesis for images by sampling without replacementPoster3 citations
178. Application of kernel hypothesis testing on set-valued dataPoster2 citations
179. CORe: Capitalizing On Rewards in Bandit ExplorationPoster2 citations
180. Dependency in DAG models with hidden variablesPoster2 citations
181. Hierarchical learning of Hidden Markov Models with clustering regularizationPoster2 citations
182. Non-PSD matrix sketching with applications to regression and optimizationPoster2 citations
183. On the distributional properties of adaptive gradientsPoster2 citations
184. Sequential core-set Monte CarloPoster2 citations
185. Statistical mechanical analysis of neural network pruningPoster2 citations
186. Time-variant variational transfer for value functionsPoster2 citations
187. Variance reduction in frequency estimators via control variates methodPoster2 citations
188. XOR-SGD: provable convex stochastic optimization for decision-making under uncertaintyPoster2 citations
189. A heuristic for statistical seriationPoster1 citations
190. Gradient-based optimization for multi-resource spatial coverage problemsPoster1 citations
191. Identifying regions of trusted predictionsPoster1 citations
192. Path-BN: Towards effective batch normalization in the Path Space for ReLU networksPoster1 citations
193. Stochastic model for sunk cost biasPoster1 citations
194. Structured sparsification with joint optimization of group convolution and channel shufflePoster1 citations
195. When is particle filtering efficient for planning in partially observed linear dynamical systems?Poster1 citations
196. Dimension reduction for data with heterogeneous missingnessPoster
197. Generalized parametric path problemsPoster
198. Geometric rates of convergence for kernel-based sampling algorithmsPoster
199. Graph-based semi-supervised learning through the lens of safetyPoster
200. Inference of causal effects when control variables are unknownPoster
201. Learning in Multi-Player Stochastic GamesPoster
202. PALM: Probabilistic area loss Minimization for Protein Sequence AlignmentPoster
203. Proceedings of the thirty-seventh conference on Uncertainty in Artificial Intelligence — PrefacePoster
204. Robust principal component analysis for generalized multi-view modelsPoster
205. Subset-of-data variational inference for deep Gaussian-processes regressionPoster

Looking for submission deadlines instead? See the conference deadline calendar.