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Probabilistic Modeling

363 directly classified papers

Papers per year

Papers

Impartial Multi-task Representation Learning via Variance-invariant Probabilistic Decoding ACL 2025
Reducing Unimodal Bias in Multi-Modal Semantic Segmentation with Multi-Scale Functional Entropy Regularization ICCV 2025
Doubling Your Data in Minutes: Ultra-fast Tabular Data Generation via LLM-Induced Dependency Graphs EMNLP 2025
Extending Complex Logical Queries on Uncertain Knowledge Graphs ACL 2025
DisCoPatch: Taming Adversarially-driven Batch Statistics for Improved Out-of-Distribution Detection ICCV 2025
Neural Topic Modeling via Contextual and Graph Information Fusion EMNLP 2025
Predicting Median, Disagreement and Noise Label in Ordinal Word-in-Context Data COLING 2025
Learning Structural Causal Models from Ordering: Identifiable Flow Models AAAI 2025
Community-Aware Variational Autoencoder for Continuous Dynamic Networks AAAI 2025
Improving Model Probability Calibration by Integration of Large Data Sources with Biased Labels AAAI 2025
G2SF: Geometry-Guided Score Fusion for Multimodal Industrial Anomaly Detection ICCV 2025
Optimizing Hidden Markov Language Models: An Empirical Study of Reparameterization and Initialization Techniques NAACL 2025
Error Detection for Multimodal Classification NAACL 2025
Learning Causal Transition Matrix for Instance-dependent Label Noise AAAI 2025
Extremal graphical modeling with latent variables via convex optimization JMLR 2025
Deep-change at CoMeDi: the Cross-Entropy Loss is not All You Need COLING 2025
A New Statistical Model of Star Speckles for Learning to Detect and Characterize Exoplanets in Direct Imaging Observations CVPR 2025
A Conditional Probability Framework for Compositional Zero-shot Learning ICCV 2025
A Variational Autoencoder for Neural Temporal Point Processes with Dynamic Latent Graphs AAAI 2024
Disentangling the Roles of Distinct Cell Classes with Cell-Type Dynamical Systems NIPS 2024
Considering Nonstationary within Multivariate Time Series with Variational Hierarchical Transformer for Forecasting AAAI 2024
SimCalib: Graph Neural Network Calibration Based on Similarity between Nodes AAAI 2024
Sparse Bayesian Generative Modeling for Compressive Sensing NIPS 2024
Categorical Flow Matching on Statistical Manifolds NIPS 2024
Data-Driven Knowledge-Aware Inference of Private Information in Continuous Double Auctions AAAI 2024