Daniel Lee

with Der · 2005

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 Daniel Lee trusts

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

  1. Radford M. Neal (in Probabilistic & Bayesian Methods)

Papers from Daniel Lee's perspective

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

  1. Bayesian learning for neural networks
  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