Artem Molchanov

Artificial Intelligence · 2016–2019

A researcher in the Science corpus: 3 papers; trusts 31 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 39 citations into it
• Computer Vision and Pattern Recognition — 26 citations into it
• Reinforcement Learning — 23 citations into it
• Optimization & Training — 18 citations into it
• Representation & Self-Supervised Learning — 8 citations into it
• Model Architectures — 6 citations into it

Whom Artem Molchanov trusts overall

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

1. Ronald J. Williams
2. Yoshua Bengio
3. Geoffrey E. Hinton
4. Sergey Levine
5. Yann LeCun
6. Diederik P. Kingma
7. Richard S. Sutton
8. Pieter Abbeel
9. Andrew Y. Ng
10. John Schulman

Papers from Artem Molchanov's perspective

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

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Gradient-based learning applied to document recognition
5. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Learning Multiple Layers of Features from Tiny Images
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Meta Learning via Learned Loss (2019) — 126 citations
• Generalized Inner Loop Meta-Learning (2019) — 169 citations
• BiGS: BioTac Grasp Stability Dataset (2016) — 33 citations