Misha Khalman

Artificial Intelligence · 2023–2024

A researcher in the Science corpus: 3 papers; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Misha Khalman trusts overall

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

  1. Radford M. Neal
  2. Noam Shazeer
  3. Chin-Yew Lin
  4. John Schulman

Papers from Misha Khalman's perspective

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

  1. Language Models are Unsupervised Multitask Learners
  2. Language Models are Few-Shot Learners (Neural Information Processing Systems)
  3. Attention is All you Need (Neural Information Processing Systems)
  4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  5. ImageNet classification with deep convolutional neural networks
  6. Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer (Journal of machine learning research)
  7. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  8. Long Short-Term Memory
  9. Proximal Policy Optimization Algorithms (arXiv.org)
  10. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)

Their papers