Utkarsh Sharma
Artificial Intelligence · 2020–2021
A researcher in the Science corpus: 2 papers; trusts 13 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 52 citations into it
- Computer Vision and Pattern Recognition — 28 citations into it
- Optimization & Training — 9 citations into it
- Representation & Self-Supervised Learning — 9 citations into it
- Statistics and Probability — 8 citations into it
- Large Language Models — 7 citations into it
- Probabilistic & Bayesian Methods — 6 citations into it
Whom Utkarsh Sharma trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Alex Krizhevsky
- Alec Radford
- Diederik P. Kingma
- Stergios B. Fotopoulos
- Elizaveta Levina
- Geoffrey E. Hinton
- Jimmy Ba
- Yoshua Bengio
- Ilya Sutskever
- Alessio Ansuini
Who trusts Utkarsh Sharma overall
Papers from Utkarsh Sharma's perspective
Ordered by how strongly the researchers Utkarsh Sharma trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Attention is All you Need (Neural Information Processing Systems)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- Learning Multiple Layers of Features from Tiny Images
- ImageNet: A large-scale hierarchical image database
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
Their papers
- Explaining neural scaling laws (2021) — 491 citations
- A Neural Scaling Law from the Dimension of the Data Manifold (2020) — 69 citations