Eric Lippert

2020

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 Eric Lippert trusts

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

1. Vivek S. Borkar (in AI for Physical Sciences)

Papers from Eric Lippert's perspective

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

1. Hybrid Monte Carlo
2. The No-U-turn sampler: adaptively setting path lengths in Hamiltonian Monte Carlo
3. Automatic differentiation in PyTorch
4. Stan: A Probabilistic Programming Language
5. Pyro: Deep Universal Probabilistic Programming
6. BLOG: Probabilistic Models with Unknown Objects
7. Equation of State Calculations by Fast Computing Machines
8. Lightweight Implementations of Probabilistic Programming Languages Via Transformational Compilation
9. Probabilistic models with unknown objects
10. Bayesian Learning via Stochastic Dynamics

Their papers

• Bean Machine: A Declarative Probabilistic Programming Language For Efficient Programmable Inference (2020) — 15 citations