Karl Cobbe

Artificial Intelligence · 2018–2024

A researcher in the Science corpus: 6 papers; trusts 26 researchers and is trusted by 38 researchers here, as inferred from the citation graph.

Subfields

Whom Karl Cobbe trusts overall

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

  1. Sepp Hochreiter
  2. Diederik P. Kingma
  3. John Schulman
  4. Yoshua Bengio
  5. Geoffrey E. Hinton
  6. J. Urgen Schmidhuber
  7. Joseph B. Kruskal
  8. Alex Krizhevsky
  9. Ilya Sutskever
  10. Jimmy Ba

Who trusts Karl Cobbe overall

  1. Roberta Raileanu
  2. Kimin Lee
  3. Minqi Jiang
  4. Danijar Hafner
  5. Rishabh Agarwal
  6. Arthur Juliani
  7. Zhihong Shao
  8. Yao Fu
  9. Sae-Young Chung
  10. Michael Laskin

Papers from Karl Cobbe's perspective

Ordered by how strongly the researchers Karl Cobbe 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. Attention is All you Need (Neural Information Processing Systems)
  5. Long Short-Term Memory
  6. Gradient-based learning applied to document recognition
  7. ImageNet: A large-scale hierarchical image database
  8. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
  9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  10. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)

Their papers