Samuel Weinbach
Artificial Intelligence · 2021–2022
A researcher in the Science corpus: 2 papers; trusts 172 researchers and is trusted by 3 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 119 citations into it
- Computer Vision and Pattern Recognition — 65 citations into it
- Large Language Models — 42 citations into it
- Natural Language Processing — 35 citations into it
- Multimodal Learning — 22 citations into it; #880 of 1,211 by trust here, #1,076 by citations
Whom Samuel Weinbach trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Kaiming He
- Geoffrey E. Hinton
- Alec Radford
- Alex Krizhevsky
- Diederik P. Kingma
- Yoshua Bengio
- Ilya Sutskever
- Ross B. Girshick
- Shaoqing Ren
- Yann LeCun
Who trusts Samuel Weinbach overall
Papers from Samuel Weinbach's perspective
Ordered by how strongly the researchers Samuel Weinbach trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Attention is All you Need (Neural Information Processing Systems)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- Gradient-based learning applied to document recognition
- ImageNet Large Scale Visual Recognition Challenge
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- GPT-NeoX-20B: An Open-Source Autoregressive Language Model (2022) — 1,029 citations
- MAGMA - Multimodal Augmentation of Generative Models through Adapter-based Finetuning (2021) — 112 citations