MCMC using Hamiltonian dynamics

9 June 2012

Papers citing "MCMC using Hamiltonian dynamics"

50 / 1,031 papers shown

Title
Bayesian causal discovery from unknown general interventions Alessandro Mascaro F. Castelletti 8 1 0 01 Dec 2023
Accelerating Neural Field Training via Soft Mining Shakiba Kheradmand Daniel Rebain Gopal Sharma Hossam N. Isack Abhishek Kar Andrea Tagliasacchi Kwang Moo Yi 35 4 0 29 Nov 2023
Maximum Entropy Model Correction in Reinforcement Learning Amin Rakhsha Mete Kemertas Mohammad Ghavamzadeh Amir-massoud Farahmand 15 1 0 29 Nov 2023
An Empirical Bayes Framework for Open-Domain Dialogue Generation Jing Yang Lee Kong Aik Lee Woon-Seng Gan BDL 6 0 0 18 Nov 2023
Fuse It or Lose It: Deep Fusion for Multimodal Simulation-Based Inference Marvin Schmitt Stefan T. Radev Paul-Christian Burkner 44 5 0 17 Nov 2023
Direct Amortized Likelihood Ratio Estimation Adam D. Cobb Brian Matejek Daniel Elenius Anirban Roy Susmit Jha 11 2 0 17 Nov 2023
Variational Temporal IRT: Fast, Accurate, and Explainable Inference of Dynamic Learner Proficiency Yunsung Kim Sreechan Sankaranarayanan Chris Piech Candace Thille VLM 37 2 0 14 Nov 2023
Approximating Langevin Monte Carlo with ResNet-like Neural Network architectures Charles Miranda Janina Enrica Schutte David Sommer Martin Eigel 18 3 0 06 Nov 2023
Diffusion Models for Reinforcement Learning: A Survey Zhengbang Zhu Hanye Zhao Haoran He Yichao Zhong Shenyu Zhang Haoquan Guo Tingting Chen Weinan Zhang 27 59 0 02 Nov 2023
Rethinking Variational Inference for Probabilistic Programs with Stochastic Support Tim Reichelt C. Ong Tom Rainforth 14 2 0 01 Nov 2023
An Embedded Diachronic Sense Change Model with a Case Study from Ancient Greek Schyan Zafar Geoff K. Nicholls 19 1 0 01 Nov 2023
Diffusion models for probabilistic programming Simon Dirmeier Fernando Pérez-Cruz 53 0 0 01 Nov 2023
Bayesian Multistate Bennett Acceptance Ratio Methods Xinqiang Ding 15 3 0 31 Oct 2023
Estimating optimal PAC-Bayes bounds with Hamiltonian Monte Carlo Szilvia Ujváry Gergely Flamich Vincent Fortuin José Miguel Hernández Lobato 10 0 0 30 Oct 2023
Purify++: Improving Diffusion-Purification with Advanced Diffusion Models and Control of Randomness Boya Zhang Weijian Luo Zhihua Zhang 21 10 0 28 Oct 2023
Coreset Markov Chain Monte Carlo Naitong Chen Trevor Campbell 11 4 0 25 Oct 2023
Particle-based Variational Inference with Generalized Wasserstein Gradient Flow Ziheng Cheng Shiyue Zhang Longlin Yu Cheng Zhang BDL 26 6 0 25 Oct 2023
Bayesian imaging inverse problem with SA-Roundtrip prior via HMC-pCN sampler Jiayu Qian Yuanyuan Liu Jingya Yang Qingping Zhou 13 0 0 24 Oct 2023
Beyond Bayesian Model Averaging over Paths in Probabilistic Programs with Stochastic Support Tim Reichelt C.-H. Luke Ong Tom Rainforth 17 0 0 23 Oct 2023
Calibrating Neural Simulation-Based Inference with Differentiable Coverage Probability Maciej Falkiewicz Naoya Takeishi Imahn Shekhzadeh Antoine Wehenkel Arnaud Delaunoy Gilles Louppe Alexandros Kalousis 19 6 0 20 Oct 2023
Towards Understanding Sycophancy in Language Models Mrinank Sharma Meg Tong Tomasz Korbak D. Duvenaud Amanda Askell ... Oliver Rausch Nicholas Schiefer Da Yan Miranda Zhang Ethan Perez 209 178 0 20 Oct 2023
Neural Likelihood Approximation for Integer Valued Time Series Data Luke O'Loughlin John Maclean Andrew Black AI4TS 13 0 0 19 Oct 2023
Sensitivity-Aware Amortized Bayesian Inference Lasse Elsemüller Hans Olischläger Marvin Schmitt Paul-Christian Burkner Ullrich Kothe Stefan T. Radev 15 7 0 17 Oct 2023
Correcting model misspecification in physics-informed neural networks (PINNs) Zongren Zou Xuhui Meng George Karniadakis PINN 24 41 0 16 Oct 2023
An Introduction to the Calibration of Computer Models Richard D. Wilkinson Christopher W. Lanyon 19 0 0 13 Oct 2023
PICProp: Physics-Informed Confidence Propagation for Uncertainty Quantification Qianli Shen Wai Hoh Tang Zhun Deng Apostolos F. Psaros Kenji Kawaguchi 57 1 0 10 Oct 2023
Leveraging Self-Consistency for Data-Efficient Amortized Bayesian Inference Marvin Schmitt Desi R. Ivanova Daniel Habermann Baixu Chen Jie Jiang Stefan T. Radev FedML 22 5 0 06 Oct 2023
Grokking as a First Order Phase Transition in Two Layer Networks Noa Rubin Inbar Seroussi Z. Ringel 26 15 0 05 Oct 2023
Sampling via Gradient Flows in the Space of Probability Measures Yifan Chen Daniel Zhengyu Huang Jiaoyang Huang Sebastian Reich Andrew M. Stuart 22 13 0 05 Oct 2023
Multi-fidelity No-U-Turn Sampling Kislaya Ravi T. Neckel H. Bungartz 12 1 0 04 Oct 2023
Probabilistic Reach-Avoid for Bayesian Neural Networks Matthew Wicker Luca Laurenti A. Patané Nicola Paoletti Alessandro Abate Marta Z. Kwiatkowska 16 2 0 03 Oct 2023
A physics and data co-driven surrogate modeling method for high-dimensional rare event simulation Jianhua Xian Ziqi Wang AI4CE 20 9 0 30 Sep 2023
Diffusion Models as Stochastic Quantization in Lattice Field Theory L. Wang Gert Aarts Kai Zhou DiffM 27 14 0 29 Sep 2023
Bayesian Cramér-Rao Bound Estimation with Score-Based Models Evan Scope Crafts Xianyang Zhang Ye Zhao 11 2 0 28 Sep 2023
Improvements on Scalable Stochastic Bayesian Inference Methods for Multivariate Hawkes Process Alex Ziyu Jiang Abel Rodríguez 19 1 0 26 Sep 2023
Self-Tuning Hamiltonian Monte Carlo for Accelerated Sampling H. Christiansen Federico Errica Francesco Alesiani 35 6 0 24 Sep 2023
Multi-fidelity climate model parameterization for better generalization and extrapolation Mohamed Aziz Bhouri Liran Peng Michael S. Pritchard Pierre Gentine AI4CE 24 4 0 19 Sep 2023
Affine Invariant Ensemble Transform Methods to Improve Predictive Uncertainty in Neural Networks Diksha Bhandari Jakiw Pidstrigach Sebastian Reich 20 1 0 09 Sep 2023
Iterative Multi-granular Image Editing using Diffusion Models K. J. Joseph Prateksha Udhayanan Tripti Shukla Aishwarya Agarwal Srikrishna Karanam Koustava Goswami Balaji Vasan Srinivasan DiffM 22 16 0 01 Sep 2023
Noise-Free Sampling Algorithms via Regularized Wasserstein Proximals Hongwei Tan Stanley Osher Wuchen Li 19 7 0 28 Aug 2023
Renormalizing Diffusion Models Jordan S. Cotler Semon Rezchikov DiffM AI4CE 27 11 0 23 Aug 2023
Semi-Implicit Variational Inference via Score Matching Longlin Yu C. Zhang 11 10 0 19 Aug 2023
Perfect simulation from unbiased simulation G. Leigh Wen-Hsi Yang Montana Wickens Amanda R. Northrop Queensland Department of Agriculture 10 1 0 14 Aug 2023
Likelihood-ratio-based confidence intervals for neural networks Laurens Sluijterman Eric Cator Tom Heskes UQCV 22 0 0 04 Aug 2023
Quantification of Predictive Uncertainty via Inference-Time Sampling Katarína Tóthová Lubor Ladicky D. Thul Marc Pollefeys E. Konukoglu UQCV 14 0 0 03 Aug 2023
An Agent-Based Model Framework for Utility-Based Cryptoeconomies Kiran Karra Tom Mellan Maria Silva Juan P. Madrigal-Cianci Axel Cubero Cortes Zixuan Zhang 8 1 0 27 Jul 2023
Explicit Constraints on the Geometric Rate of Convergence of Random Walk Metropolis-Hastings Riddhiman Bhattacharya Galin L. Jones 15 2 0 21 Jul 2023
Field-Level Inference with Microcanonical Langevin Monte Carlo Adrian E Bayer U. Seljak Chirag Modi 26 9 0 18 Jul 2023
Characterization of partial wetting by CMAS droplets using multiphase many-body dissipative particle dynamics and data-driven discovery based on PINNs Elham Kiyani M. Kooshkbaghi K. Shukla R. Koneru Zhen Li L. Bravo A. Ghoshal George Karniadakis M. Karttunen AI4CE 27 4 0 18 Jul 2023
Gaussian processes for Bayesian inverse problems associated with linear partial differential equations Tianming Bai A. Teckentrup K. Zygalakis 25 8 0 17 Jul 2023