Joshua Lockhart

Artificial Intelligence · 2018

A researcher in the Science corpus: 1 paper; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Joshua Lockhart trusts

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

  1. Guifré Vidal (in Atomic and Molecular Physics, and Optics)
  2. Alex Graves (in Probabilistic & Bayesian Methods)
  3. R. Fisher (in Statistical Learning Theory)

Papers from Joshua Lockhart's perspective

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

  1. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  2. Practical Variational Inference for Neural Networks
  3. Supervised Learning with Tensor Networks (Neural Information Processing Systems)
  4. Matrix product states, projected entangled pair states, and variational renormalization group methods for quantum spin systems
  5. THE USE OF MULTIPLE MEASUREMENTS IN TAXONOMIC PROBLEMS
  6. Quantum Computing in the NISQ era and beyond (Quantum)
  7. Deep Complex Networks
  8. Benefits of Depth in Neural Networks
  9. Quantum algorithm for solving linear systems of equations
  10. Emergence of invariance and disentangling in deep representations

Their papers