conftrace_

Bayesian & Probabilistic

5,407 papers (3 classified directly here)

Subtopics · a paper can sit in several, so these overlap

Probabilistic Modeling (3,137) Bayesian Learning (1,734) Bayesian Inference (1,087) Variational Inference (275) Bayesian Networks (103) Gaussian Processes (88)

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Papers (including subtopics)

Bayesian Optimization through Gaussian Cox Process Models for Spatio-temporal Data ICLR 2024 Bayesian Pseudo-Coresets via Contrastive Divergence UAI 2024 Bayesian Semi-structured Subspace Inference AISTATS 2024 Bayesian Structural Learning with Parametric Marginals for Count Data: An Application to Microbiota Systems JMLR 2024 Bayes-optimal learning of an extensive-width neural network from quadratically many samples NeurIPS 2024 Be Confident in What You Know: Bayesian Parameter Efficient Fine-Tuning of Vision Foundation Models NeurIPS 2024 Beta-LR: Interpretable Logical Reasoning based on Beta Distribution NAACL 2024 Better Batch for Deep Probabilistic Time Series Forecasting AISTATS 2024 Better-than-KL PAC-Bayes Bounds COLT 2024 Beyond Bayesian Model Averaging over Paths in Probabilistic Programs with Stochastic Support AISTATS 2024 Beyond Dirichlet-based Models: When Bayesian Neural Networks Meet Evidential Deep Learning UAI 2024 Beyond ELBOs: A Large-Scale Evaluation of Variational Methods for Sampling ICML 2024 Beyond IID weights: sparse and low-rank deep Neural Networks are also Gaussian Processes ICLR 2024 Beyond Single Stationary Policies: Meta-Task Players as Naturally Superior Collaborators NeurIPS 2024 Beyond the Norms: Detecting Prediction Errors in Regression Models ICML 2024 Bias Amplification in Language Model Evolution: An Iterated Learning Perspective NeurIPS 2024 Bias Detection via Signaling NeurIPS 2024 Binary Search with Distributional Predictions NeurIPS 2024 BLoB: Bayesian Low-Rank Adaptation by Backpropagation for Large Language Models NeurIPS 2024 Block Sparse Bayesian Learning: A Diversified Scheme NeurIPS 2024 Bootstrap Your Conversions: Thompson Sampling for Partially Observable Delayed Rewards UAI 2024 Boundary constrained Gaussian processes for robust physics-informed machine learning of linear partial differential equations JMLR 2024 Building Expressive and Tractable Probabilistic Generative Models: A Review IJCAI 2024 Calibrating the Confidence of Large Language Models by Eliciting Fidelity EMNLP 2024 Can Machines Learn the True Probabilities? ICML 2024