Leonard Wossnig

Artificial Intelligence · 2017–2021

A researcher in the Science corpus: 3 papers; trusts 9 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 146 citations into it; #29,705 of 35,345 by trust here, #15,542 by citations
• Atomic and Molecular Physics, and Optics — 97 citations into it; #5,367 of 7,135 by trust here, #4,402 by citations
• Optimization & Training — 15 citations into it
• Probabilistic & Bayesian Methods — 14 citations into it
• Numerical Methods & Scientific Computing — 6 citations into it

Whom Leonard Wossnig trusts overall

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

1. Diederik P. Kingma
2. Maria Schuld
3. Radford M. Neal
4. Jimmy Ba

Who trusts Leonard Wossnig overall

1. M. Cerezo
2. Zoe Holmes

Papers from Leonard Wossnig's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
3. GENERATIVE ADVERSARIAL NETS
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
5. Improved Techniques for Training GANs
6. Rethinking the Inception Architecture for Computer Vision
7. Training Products of Experts by Minimizing Contrastive Divergence
8. Gradient-based learning applied to document recognition
9. Learning Multiple Layers of Features from Tiny Images
10. Attention is All you Need (Neural Information Processing Systems)

Their papers

• The Variational Quantum Eigensolver: A review of methods and best practices (2021) — 1,215 citations
• An initialization strategy for addressing barren plateaus in parametrized quantum circuits (2019) — 514 citations
• Quantum machine learning: a classical perspective (2017) — 544 citations