bayesian sampling

AgentSwift: Efficient LLM Agent Design via Value-Guided Hierarchical Search AAAI 2026 Sampling and Estimation on Manifolds using the Langevin Diffusion JMLR 2025 Geometric No-U-Turn Samplers: Concepts and Evaluation PGM 2024 On cyclical MCMC sampling AISTATS 2024 Robust Approximate Sampling via Stochastic Gradient Barker Dynamics AISTATS 2024 The Bayesian sampling in a canonical recurrent circuit with a diversity of inhibitory interneurons NeurIPS 2024 Low-Precision Stochastic Gradient Langevin Dynamics ICML 2022 Neural ensemble search via Bayesian sampling UAI 2022 Bayes-TrEx: a Bayesian Sampling Approach to Model Transparency by Example AAAI 2021 Langevin Monte Carlo: random coordinate descent and variance reduction JMLR 2021 AMAGOLD: Amortized Metropolis Adjustment for Efficient Stochastic Gradient MCMC AISTATS 2020 Variance Reduction in Stochastic Particle-Optimization Sampling ICML 2020 Self-Adversarially Learned Bayesian Sampling AAAI 2019 Adaptive Bayesian Sampling with Monte Carlo EM NeurIPS 2017 Langevin Dynamics with Continuous Tempering for Training Deep Neural Networks NeurIPS 2017 Covariance-Controlled Adaptive Langevin Thermostat for Large-Scale Bayesian Sampling NeurIPS 2015 Bayesian Sampling Using Stochastic Gradient Thermostats NeurIPS 2014 Auxiliary-variable Exact Hamiltonian Monte Carlo Samplers for Binary Distributions NeurIPS 2013 Optimistic Bayesian Sampling in Contextual-Bandit Problems JMLR 2012 Quasi-Newton Methods for Markov Chain Monte Carlo NeurIPS 2011