Tao Kong

Artificial Intelligence · with Li · 2023

A researcher in the Science corpus: 2 papers; trusts 14 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Tao Kong trusts

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

  1. Pierre Sermanet (in Computer Vision and Pattern Recognition)
  2. Pieter Abbeel (in Computer Vision and Pattern Recognition)
  3. Corey Lynch (in Computer Vision and Pattern Recognition)
  4. Sergey Levine (in Artificial Intelligence)
  5. Wolfram Burgard (in Computer Vision and Pattern Recognition)
  6. Oier Mees (in Artificial Intelligence)
  7. Ilya Loshchilov (in Optimization & Training)
  8. Lukás Hermann (in Computer Vision and Pattern Recognition)
  9. Kaiming He (in Computer Vision and Pattern Recognition)
  10. Frank Hutter (in Optimization & Training)

Papers from Tao Kong's perspective

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

  1. Attention is All you Need (Neural Information Processing Systems)
  2. Long Short-Term Memory
  3. Language Models are Few-Shot Learners (Neural Information Processing Systems)
  4. Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer (Journal of machine learning research)
  5. Learning Transferable Visual Models From Natural Language Supervision (International Conference on Machine Learning)
  6. Decoupled Weight Decay Regularization
  7. Improving Language Understanding by Generative Pre-Training
  8. SGDR: Stochastic Gradient Descent with Warm Restarts
  9. EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
  10. Deep visual foresight for planning robot motion

Their papers