probabilistic modeling

851 papers

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PM

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bayesian inference (1904) variational inference (2069) probabilistic model (476) graphical model (863) uncertainty quantification (1365) generative model (2889) bayesian network (378) causal inference (1619) latent variable model (564) probabilistic inference (310)

Papers

A Variational Autoencoder for Neural Temporal Point Processes with Dynamic Latent Graphs AAAI 2024

TreeVI: Reparameterizable Tree-structured Variational Inference for Instance-level Correlation Capturing NIPS 2024

Probabilistic Speech-Driven 3D Facial Motion Synthesis: New Benchmarks Methods and Applications CVPR 2024

PyRater: A Python Toolkit for Annotation Analysis COLING 2024

Benchmarking LLMs via Uncertainty Quantification NIPS 2024

Interpreting Predictive Probabilities: Model Confidence or Human Label Variation? EACL 2024

Mutual Information Estimation via Normalizing Flows NIPS 2024

QUITE: Quantifying Uncertainty in Natural Language Text in Bayesian Reasoning Scenarios EMNLP 2024

Blind Zero-Shot Audio Restoration: A Variational Autoencoder Approach for Denoising and Inpainting INTERSPEECH 2024

Neural Conditional Probability for Uncertainty Quantification NIPS 2024

Constrained Probabilistic Mask Learning for Task-Specific Undersampled MRI Reconstruction WACV 2024

GAD-PVI: A General Accelerated Dynamic-Weight Particle-Based Variational Inference Framework AAAI 2024

Global and Local Hierarchical Prompt Tuning Framework for Multi-level Implicit Discourse Relation Recognition COLING 2024

Evaluating n-Gram Novelty of Language Models Using Rusty-DAWG EMNLP 2024

Seeing Unseen: Discover Novel Biomedical Concepts via Geometry-Constrained Probabilistic Modeling CVPR 2024

Bayesian-guided Label Mapping for Visual Reprogramming NIPS 2024

Modelling Variability in Human Annotator Simulation ACL 2024

Negative-Binomial Randomized Gamma Dynamical Systems for Heterogeneous Overdispersed Count Time Sequences IJCAI 2024

A Theory of Non-acyclic Generative Flow Networks AAAI 2024

Towards Understanding Future: Consistency Guided Probabilistic Modeling for Action Anticipation AAAI 2024

The Evidence Contraction Issue in Deep Evidential Regression: Discussion and Solution AAAI 2024

Controlling Multiple Errors Simultaneously with a PAC-Bayes Bound NIPS 2024

Peer Neighborhood Mechanisms: A Framework for Mechanism Generalization AAAI 2024

SPD-DDPM: Denoising Diffusion Probabilistic Models in the Symmetric Positive Definite Space AAAI 2024

Probabilistic Modeling for Sequences of Sets in Continuous-Time AISTATS 2024