Vijay Anand Korthikanti
Artificial Intelligence · 2021–2022
A researcher in the Science corpus: 4 papers; trusts 7 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 90 citations into it
- Computer Vision and Pattern Recognition — 48 citations into it
- Efficiency & Compression — 38 citations into it
- Hardware and Architecture — 25 citations into it
- Model Architectures — 10 citations into it
Whom Vijay Anand Korthikanti trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Samyam Rajbhandari
- D. Narayanan
- Jeff Rasley
- Matei A. Zaharia
- Olatunji Ruwase
- Mohammad Shoeybi
- Noam Shazeer
- Minjie Wang
- Yanping Huang
- M. Patwary
Who trusts Vijay Anand Korthikanti overall
Papers from Vijay Anand Korthikanti's perspective
Ordered by how strongly the researchers Vijay Anand Korthikanti 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)
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Language Models are Few-Shot Learners (Neural Information Processing Systems)
- Long Short-Term Memory
- Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer (Journal of machine learning research)
- 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
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- ImageNet: A large-scale hierarchical image database
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
- Reducing Activation Recomputation in Large Transformer Models (2022) — 492 citations
- Efficient Large-Scale Language Model Training on GPU Clusters (2021) — 108 citations