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Methodology
← Bayesian & Probabilistic
Artificial Intelligence
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Bayesian & Probabilistic
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Probabilistic Modeling
2591 directly classified papers
Papers per year
2000: 1
2001: 1
2002: 2
2003: 3
2004: 3
2005: 8
2006: 31
2007: 34
2008: 43
2009: 38
2010: 78
2011: 56
2012: 76
2013: 94
2014: 103
2015: 87
2016: 118
2017: 128
2018: 149
2019: 227
2020: 232
2021: 265
2022: 218
2023: 256
2024: 198
2025: 84
2026: 58
Papers
Robust Outlier Rejection for 3D Registration With Variational Bayes
CVPR 2023
Topological Obstructions and How to Avoid Them
NIPS 2023
Not all Strongly Rayleigh Distributions Have Small Probabilistic Generating Circuits
ICML 2023
Learning Noisy OR Bayesian Networks with Max-Product Belief Propagation
ICML 2023
Neural Diffusion Processes
ICML 2023
On Second-Order Scoring Rules for Epistemic Uncertainty Quantification
ICML 2023
SynJax: Structured Probability Distributions for JAX
EMNLP 2023
FLatS: Principled Out-of-Distribution Detection with Feature-Based Likelihood Ratio Score
EMNLP 2023
Under-Counted Tensor Completion with Neural Incorporation of Attributes
ICML 2023
What Comes Next? Evaluating Uncertainty in Neural Text Generators Against Human Production Variability
EMNLP 2023
Cognitive Dissonance: Why Do Language Model Outputs Disagree with Internal Representations of Truthfulness?
EMNLP 2023
Uncertainty-Aware Bootstrap Learning for Joint Extraction on Distantly-Supervised Data
ACL 2023
Just Ask for Calibration: Strategies for Eliciting Calibrated Confidence Scores from Language Models Fine-Tuned with Human Feedback
EMNLP 2023
A Probabilistic Framework for Discovering New Intents
ACL 2023
CO-BED: Information-Theoretic Contextual Optimization via Bayesian Experimental Design
ICML 2023
CICL_DMS at SemEval-2023 Task 11: Learning With Disagreements (Le-Wi-Di)
ACL 2023
Adversarial Counterfactual Visual Explanations
CVPR 2023
Score-Based Learning of Graphical Event Models with Background Knowledge Augmentation
AAAI 2023
Probabilistic Reasoning and Learning for Trustworthy AI
AAAI 2023
Compositional Probabilistic and Causal Inference using Tractable Circuit Models
AISTATS 2023
A Probabilistic Graph Diffusion Model for Source Localization (Student Abstract)
AAAI 2023
On the Calibration and Uncertainty with Pólya-Gamma Augmentation for Dialog Retrieval Models
AAAI 2023
Sentiment as an Ordinal Latent Variable
EACL 2023
Reinforcement Causal Structure Learning on Order Graph
AAAI 2023
Editing Boolean Classifiers: A Belief Change Perspective
AAAI 2023
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