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Publication search results
found 132 matches
- 2024
- Parag C. Pendharkar:
A Markov Chain Genetic Algorithm Approach for Non-Parametric Posterior Distribution Sampling of Regression Parameters. Algorithms 17(3): 111 (2024) - Cheng-Der Fuh, Chuan-Ju Wang, Chen-Hung Pai:
Markov chain importance sampling for minibatches. Mach. Learn. 113(2): 789-814 (2024) - Yihan Fu, Daijing Shi, Anjunyi Fan, Wenshuo Yue, Yuchao Yang, Ru Huang, Bonan Yan:
Probabilistic Compute-in-Memory Design for Efficient Markov Chain Monte Carlo Sampling. IEEE Trans. Circuits Syst. I Regul. Pap. 71(2): 703-716 (2024) - Ismail Cosandal, Nail Akar, Sennur Ulukus:
Modeling AoII in Push- and Pull-Based Sampling of Continuous Time Markov Chains. CoRR abs/2401.04098 (2024) - Alexandros E. Tzikas, Licio Romao, Mert Pilanci, Alessandro Abate, Mykel J. Kochenderfer:
Distributed Markov Chain Monte Carlo Sampling based on the Alternating Direction Method of Multipliers. CoRR abs/2401.15838 (2024) - 2023
- Moien Barkhori Mehni, Mohammad Barkhori Mehni:
Reliability analysis with cross-entropy based adaptive Markov chain importance sampling and control variates. Reliab. Eng. Syst. Saf. 231: 109014 (2023) - Jeroen Huijben, Viresh Patel, Guus Regts:
Sampling from the low temperature Potts model through a Markov chain on flows. Random Struct. Algorithms 62(1): 219-239 (2023) - Vishwaraj Doshi, Jie Hu, Do Young Eun:
Self-Repellent Random Walks on General Graphs - Achieving Minimal Sampling Variance via Nonlinear Markov Chains. ICML 2023: 8403-8423 - Vishwaraj Doshi, Jie Hu, Do Young Eun:
Self-Repellent Random Walks on General Graphs - Achieving Minimal Sampling Variance via Nonlinear Markov Chains. CoRR abs/2305.05097 (2023) - George Miloshevich, Dario Lucente, Pascal Yiou, Freddy Bouchet:
Extreme heatwave sampling and prediction with analog Markov chain and comparisons with deep learning. CoRR abs/2307.09060 (2023) - Yihan Fu, Daijing Shi, Anjunyi Fan, Wenshuo Yue, Yuchao Yang, Ru Huang, Bonan Yan:
Probabilistic Compute-in-Memory Design For Efficient Markov Chain Monte Carlo Sampling. CoRR abs/2307.10866 (2023) - Giulia Preti, Gianmarco De Francisci Morales, Matteo Riondato:
An impossibility result for Markov Chain Monte Carlo sampling from micro-canonical bipartite graph ensembles. CoRR abs/2308.10838 (2023) - 2022
- Jacob Neumann, Yen Ting Lin, Abhishek Mallela, Ely F. Miller, Joshua Colvin, Abell T. Duprat, Ye Chen, William S. Hlavacek, Richard G. Posner:
Implementation of a practical Markov chain Monte Carlo sampling algorithm in PyBioNetFit. Bioinform. 38(6): 1770-1772 (2022) - Ivette Raices Cruz, Johan Lindström, Matthias C. M. Troffaes, Ullrika Sahlin:
Iterative importance sampling with Markov chain Monte Carlo sampling in robust Bayesian analysis. Comput. Stat. Data Anal. 176: 107558 (2022) - Yanzhong Wang, Bin Xie, Shiyuan E:
Adaptive relevance vector machine combined with Markov-chain-based importance sampling for reliability analysis. Reliab. Eng. Syst. Saf. 220: 108287 (2022) - Najmeh Abedzadeh, Matthew Jacobs:
Using Markov Chain Monte Carlo Algorithm for Sampling Imbalance Binary IDS Datasets. ICCCN 2022: 1-7 - Daniel Tang, Nick Malleson:
Data assimilation with agent-based models using Markov chain sampling. CoRR abs/2205.01616 (2022) - 2021
- Ingmar Schuster, Ilja Klebanov:
Markov Chain Importance Sampling - A Highly Efficient Estimator for MCMC. J. Comput. Graph. Stat. 30(2): 260-268 (2021) - Wendy K. Tam Cho, Yan Y. Liu:
A parallel evolutionary multiple-try metropolis Markov chain Monte Carlo algorithm for sampling spatial partitions. Stat. Comput. 31(1): 10 (2021) - Chris Cannella, Mohammadreza Soltani, Vahid Tarokh:
Projected Latent Markov Chain Monte Carlo: Conditional Sampling of Normalizing Flows. ICLR 2021 - Zheng Wang, Yili Xia, Shanxiang Lyu, Cong Ling:
Reinforcement Learning-Aided Markov Chain Monte Carlo For Lattice Gaussian Sampling. ITW 2021: 1-5 - Jeroen Huijben, Viresh Patel, Guus Regts:
Sampling from the low temperature Potts model through a Markov chain on flows. CoRR abs/2103.07360 (2021) - Marylou Gabrié, Grant M. Rotskoff, Eric Vanden-Eijnden:
Efficient Bayesian Sampling Using Normalizing Flows to Assist Markov Chain Monte Carlo Methods. CoRR abs/2107.08001 (2021) - 2020
- Pieter Kleer, Viresh Patel, Fabian Stroh:
Switch-Based Markov Chains for Sampling Hamiltonian Cycles in Dense Graphs. Electron. J. Comb. 27(4): 4 (2020) - Xiaoli Jia, Peilin Liu, Sumxin Jiang:
Speech Compressive Sampling Using Approximate Message Passing and a Markov Chain Prior. Sensors 20(16): 4609 (2020) - Yousef El-Laham, Petar M. Djuric, Mónica F. Bugallo:
Enhanced Mixture Population Monte Carlo Via Stochastic Optimization and Markov Chain Monte Carlo Sampling. ICASSP 2020: 5475-5479 - Priyesh Shukla, Ahish Shylendra, Theja Tulabandhula, Amit Ranjan Trivedi:
MC2RAM: Markov Chain Monte Carlo Sampling in SRAM for Fast Bayesian Inference. ISCAS 2020: 1-5 - Annika Meyer, Jonas Walter, Martin Lauer:
Fast Lane-Level Intersection Estimation using Markov Chain Monte Carlo Sampling and B-Spline Refinement. IV 2020: 71-76 - Thomas Dalgaty, Niccolo Castellani, Damien Querlioz, Elisa Vianello:
In-situ learning harnessing intrinsic resistive memory variability through Markov Chain Monte Carlo Sampling. CoRR abs/2001.11426 (2020) - Priyesh Shukla, Ahish Shylendra, Theja Tulabandhula, Amit Ranjan Trivedi:
MC2RAM: Markov Chain Monte Carlo Sampling in SRAM for Fast Bayesian Inference. CoRR abs/2003.02629 (2020)
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