Rika Antonova

Artificial Intelligence · 2017–2023

A researcher in the Science corpus: 3 papers; trusts 13 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Rika Antonova trusts overall

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

  1. John Schulman
  2. Sergey Levine
  3. Hartmut Geyer
  4. Roberto Calandra
  5. Pieter Abbeel
  6. Geoffrey E. Hinton
  7. Matthew Tesch
  8. Diederik P. Kingma
  9. Jan Peters
  10. Yoshua Bengio

Who trusts Rika Antonova overall

  1. Maximilian Balandat
  2. Ziwen Zhuang
  3. Ilija Radosavovic
  4. Zipeng Fu
  5. OpenAI
  6. Brian Karrer

Papers from Rika Antonova's perspective

Ordered by how strongly the researchers Rika Antonova 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. ImageNet: A large-scale hierarchical image database
  7. Gradient-based learning applied to document recognition
  8. Learning Multiple Layers of Features from Tiny Images
  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