M. Bokdam

Physical Review Letters · 2019

A researcher in the Science corpus: 1 paper; trusts 1 researcher and is trusted by 0 researchers here, as inferred from the citation graph.

Whom M. Bokdam trusts

Their strongest outbound trust, strongest first, inferred from their citations.

1. Radford M. Neal (in Computer Vision and Pattern Recognition)

Papers from M. Bokdam's perspective

Ordered by how strongly the researchers M. Bokdam trusts endorse each paper. Same corpus, a different order for every researcher.

1. Pattern Recognition and Machine Learning
2. Exponential convergence of Langevin distributions and their discrete approximations
3. Optimal scaling for various Metropolis-Hastings algorithms
4. Riemannian Manifold Hamiltonian Monte Carlo
5. Honest Exploration of Intractable Probability Distributions via Markov Chain Monte Carlo
6. QUANTITATIVE CONVERGENCE RATES OF MARKOV CHAINS: A SIMPLE ACCOUNT
7. Sampling from multimodal distributions using tempered transitions
8. Weak convergence and optimal scaling of random walk Metropolis algorithms
9. Sampling-Based Approaches to Calculating Marginal Densities
10. On adaptive Markov chain Monte Carlo algorithms

Their papers

• Phase Transitions of Hybrid Perovskites Simulated by Machine-Learning Force Fields Trained on the Fly with Bayesian Inference. (2019) — 335 citations