Christa Zoufal
Artificial Intelligence · 2019–2023
A researcher in the Science corpus: 4 papers; trusts 32 researchers and is trusted by 1 researcher here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 120 citations into it; #34,114 of 35,345 by trust here, #21,316 by citations
- Atomic and Molecular Physics, and Optics — 43 citations into it; #6,881 of 7,135 by trust here, #6,251 by citations
- Computational Theory and Mathematics — 36 citations into it
- Optimization & Training — 12 citations into it
- Generative Models — 11 citations into it
- Computer Vision and Pattern Recognition — 10 citations into it
- Scaling & Learning Theory — 9 citations into it
- Probabilistic & Bayesian Methods — 7 citations into it
Whom Christa Zoufal trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Kaiming He
- Shun-ichi Amari
- Stefan Woerner
- Ian J. Goodfellow
- Geoffrey E. Hinton
- Kenji Fukumizu
- Yoshua Bengio
- Jin-Guo Liu
- Farrokh Vatan
Who trusts Christa Zoufal overall
Papers from Christa Zoufal's perspective
Ordered by how strongly the researchers Christa Zoufal trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- The power of quantum neural networks (2020) — 1,167 citations
- Quantum Generative Adversarial Networks for learning and loading random distributions (2019) — 616 citations
- Challenges and opportunities in quantum optimization (2023) — 341 citations
- Option Pricing using Quantum Computers (2019) — 328 citations