Julie Bernauer
2007–2022
A researcher in the Science corpus: 3 papers; trusts 0 researchers and is trusted by 2 researchers here, as inferred from the citation graph.
Whom Julie Bernauer trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
Who trusts Julie Bernauer overall
- Sankar Basu
- Irina S. Moreira
- Iain H. Moal
- Björn Wallner
- Pedro Alexandrino Fernandes
- Mieczyslaw Torchala
Papers from Julie Bernauer's perspective
Ordered by how strongly the researchers Julie Bernauer trusts endorse each paper. Same corpus, a different order for every researcher.
- Attention is All you Need (Neural Information Processing Systems)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Language Models are Few-Shot Learners (Neural Information Processing Systems)
- 5分で分かる!? 有名論文ナナメ読み:Jacob Devlin et al. : BERT : Pre-training of Deep Bidirectional Transformers for Language Understanding
- Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer (Journal of machine learning research)
- RoBERTa: A Robustly Optimized BERT Pretraining Approach (arXiv.org)
- Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer
- Finetuned Language Models Are Zero-Shot Learners
- PyTorch: An Imperative Style, High-Performance Deep Learning Library
- Switch Transformers: Scaling to Trillion Parameter Models with Simple and Efficient Sparsity (Journal of machine learning research)
Their papers
- Using DeepSpeed and Megatron to Train Megatron-Turing NLG 530B, A Large-Scale Generative Language Model (2022) — 859 citations
- Efficient Large-Scale Language Model Training on GPU Clusters Using Megatron-LM (2021) — 1,287 citations
- A new protein-protein docking scoring function based on interface residue properties (2007) — 67 citations