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Probabilistic Modeling

2591 directly classified papers

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Papers

Scalable gradient matching based on state space Gaussian Processes ACML 2021
Post-hoc loss-calibration for Bayesian neural networks UAI 2021
Variational Multi-Task Learning with Gumbel-Softmax Priors NIPS 2021
Bayesian Inference for Optimal Transport with Stochastic Cost ACML 2021
On the Convex Combination of Determinantal Point Processes ACML 2021
Probabilistic, Structure-Aware Algorithms for Improved Variety, Accuracy, and Coverage of AMR Alignments ACL 2021
DAGSurv: Directed Ayclic Graph Based Survival Analysis Using Deep Neural Networks ACML 2021
Causal Hidden Markov Model for Time Series Disease Forecasting CVPR 2021
Retrofitting High Availability Mechanism to Tame Hybrid Transaction/Analytical Processing OSDI 2021
Modeling Sense Structure in Word Usage Graphs with the Weighted Stochastic Block Model ACL 2021
Probabilistic Box Embeddings for Uncertain Knowledge Graph Reasoning NAACL 2021
Symbol Grounding and Task Learning from Imperfect Corrections ACL 2021
Contrastive Neural Processes for Self-Supervised Learning ACML 2021
Counterfactual Mean Embeddings JMLR 2021
Spherical Confidence Learning for Face Recognition CVPR 2021
Optimal Order Simple Regret for Gaussian Process Bandits NIPS 2021
Longitudinal Variational Autoencoder AISTATS 2021
Improving Dialog Systems for Negotiation with Personality Modeling ACL 2021
Active Assessment of Prediction Services as Accuracy Surface Over Attribute Combinations NIPS 2021
PSD Representations for Effective Probability Models NIPS 2021
When in Doubt: Neural Non-Parametric Uncertainty Quantification for Epidemic Forecasting NIPS 2021
Relaxed Marginal Consistency for Differentially Private Query Answering NIPS 2021
Structure-Aware Random Fourier Kernel for Graphs NIPS 2021
Diffusion Schrödinger Bridge with Applications to Score-Based Generative Modeling NIPS 2021
De-randomizing MCMC dynamics with the diffusion Stein operator NIPS 2021