conftrace_

Bayesian & Probabilistic

4,733 papers (2 classified directly here)

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

Probabilistic Modeling (2,617) Variational Inference (898) Gaussian Processes (666) Bayesian Learning (483) Markov Chain Monte Carlo (374) Bayesian Optimization (284) Nonparametric Bayesian (174) Bayesian Networks (149) Conditional Random Fields (39)

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Papers (including subtopics)

On Divergence Measures for Training GFlowNets NeurIPS 2024 One Sample Fits All: Approximating All Probabilistic Values Simultaneously and Efficiently NeurIPS 2024 On Estimating the Gradient of the Expected Information Gain in Bayesian Experimental Design AAAI 2024 On Hardware-efficient Inference in Probabilistic Circuits UAI 2024 On Neural Networks as Infinite Tree-Structured Probabilistic Graphical Models NeurIPS 2024 On Regularized Radon-Nikodym Differentiation JMLR 2024 On the connection between Noise-Contrastive Estimation and Contrastive Divergence AISTATS 2024 On the Expressive Power of Tree-Structured Probabilistic Circuits NeurIPS 2024 On the Quantification of Image Reconstruction Uncertainty Without Training Data WACV 2024 Open problem: Convergence of single-timescale mean-field Langevin descent-ascent for two-player zero-sum games COLT 2024 Optimal estimation of Gaussian (poly)trees AISTATS 2024 Optimising Distributions with Natural Gradient Surrogates AISTATS 2024 Optimistic Bayesian Optimization with Unknown Constraints ICLR 2024 Overfitting Behaviour of Gaussian Kernel Ridgeless Regression: Varying Bandwidth or Dimensionality NeurIPS 2024 Parallel-in-Time Probabilistic Numerical ODE Solvers JMLR 2024 Parsing neural dynamics with infinite recurrent switching linear dynamical systems ICLR 2024 Partial identification of the maximum mean discrepancy with mismeasured data UAI 2024 Personalizing Reinforcement Learning from Human Feedback with Variational Preference Learning NeurIPS 2024 PG-LBO: Enhancing High-Dimensional Bayesian Optimization with Pseudo-Label and Gaussian Process Guidance AAAI 2024 PGMax: Factor Graphs for Discrete Probabilistic Graphical Models and Loopy Belief Propagation in JAX JMLR 2024 Physics-informed Neural Networks for Functional Differential Equations: Cylindrical Approximation and Its Convergence Guarantees NeurIPS 2024 Piecewise deterministic generative models NeurIPS 2024 Poisson Variational Autoencoder NeurIPS 2024 Preferential Normalizing Flows NeurIPS 2024 PrIsing: Privacy-Preserving Peer Effect Estimation via Ising Model AISTATS 2024