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https://arxiv.org/html/2506.01335v1 Neural-network-assisted Monte Carlo sampling trained by Quantum Approximate Optimization Algorithm monte carlo samplingneural network https://arxiv.org/abs/2603.22188 [2603.22188] Generalized Sequential Monte Carlo Sampling for Redistricting Simulation Abstract page for arXiv paper 2603.22188: Generalized Sequential Monte Carlo Sampling for Redistricting Simulation sequential monte carlo2603generalizedsamplingredistricting https://openreview.net/forum?id=SkW2m-3oM&referrer=%5Bthe%20profile%20of%20Veronica%20Vilaplana%5D(%2Fprofile%3Fid%3D~Veronica_Vilaplana1) Monte-Carlo Sampling applied to Multiple Instance Learning for Whole Slide Image Classification |... In this paper we propose a patch sampling strategy based on sequential Monte-Carlo methods for Whole Slide Image classification in the context of Multiple... monte carlo samplingmultiple instance learning https://arxiv.org/abs/1206.0262 [1206.0262] Fast Markov chain Monte Carlo sampling for sparse Bayesian inference in... Abstract page for arXiv paper 1206.0262: Fast Markov chain Monte Carlo sampling for sparse Bayesian inference in high-dimensional inverse problems using... markov chain monte carlo https://deepai.org/publication/meet-a-monte-carlo-exploration-exploitation-trade-off-for-buffer-sampling MEET: A Monte Carlo Exploration-Exploitation Trade-off for Buffer Sampling | DeepAI Oct 24, 2022 - 10/24/22 - Data selection is essential for any data-based optimization technique, such as Reinforcement Learning. State-of-the-art sampling s... monte carlo https://openreview.net/forum?id=YmzE3h5cGB&referrer=%5Bthe%20profile%20of%20Ziyi%20Wang%5D(%2Fprofile%3Fid%3D~Ziyi_Wang9) Enhancing Low-Precision Sampling via Stochastic Gradient Hamiltonian Monte Carlo | OpenReview Low-precision training has emerged as a promising low-cost technique to enhance the training efficiency of deep neural networks without sacrificing much... hamiltonian monte carlolow precisionenhancingsamplingvia https://deepai.org/publication/thermostat-assisted-continuous-tempered-hamiltonian-monte-carlo-for-multimodal-posterior-sampling Thermostat-assisted Continuous-tempered Hamiltonian Monte Carlo for Multimodal Posterior Sampling |... Nov 30, 2017 - 11/30/17 - In this paper, we propose a new sampling method named as the thermostat-assisted continuous-tempered Hamiltonian Monte Carlo for m... hamiltonian monte carlothermostatassistedcontinuoustempered https://openreview.net/forum?id=tmer8WAEzV Sampling with Riemannian Hamiltonian Monte Carlo in a Constrained Space | OpenReview We demonstrate for the first time that ill-conditioned, non-smooth, constrained distributions in very high dimension, can be sampled efficiently in practice,... hamiltonian monte carlosamplingriemannian https://jmlr.org/papers/v25/22-1443.html Penalized Overdamped and Underdamped Langevin Monte Carlo Algorithms for Constrained Sampling langevin monte carlooverdampedunderdamped https://arxiv.org/abs/2510.11562 [2510.11562] Optimal parallelisation strategies for flat histogram Monte Carlo sampling Abstract page for arXiv paper 2510.11562: Optimal parallelisation strategies for flat histogram Monte Carlo sampling flat histogrammonte carlo251011562optimal https://github.com/probcomp/GenPseudoMarginal.jl GitHub - probcomp/GenPseudoMarginal.jl: Sequential Monte Carlo and annealed importance sampling... Sequential Monte Carlo and annealed importance sampling inference library for Gen - probcomp/GenPseudoMarginal.jl sequential monte carlogithubjl https://www.sintef.no/en/publications/publication/0198cc471a52-76fcd1f9-5e80-4a9b-beb0-0880956213d6/ A Monte Carlo sampling procedure for rare events applied to power system reliability analysis -... https://openreview.net/forum?id=stMhi1Sn2G Accelerated Speculative Sampling Based on Tree Monte Carlo | OpenReview Speculative Sampling (SpS) has been introduced to speed up inference of large language models (LLMs) by generating multiple tokens in a single forward pass... based onmonte carloacceleratedspeculativesampling