Markus Norman Rabe
Artificial Intelligence · 2013–2023
A researcher in the Science corpus: 12 papers; trusts 192 researchers and is trusted by 24 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 211 citations into it; #8,016 of 35,345 by trust here, #7,471 by citations
- Natural Language Processing — 83 citations into it; #3,435 of 5,688 by trust here, #3,053 by citations
- Computer Vision and Pattern Recognition — 75 citations into it
- Large Language Models — 61 citations into it
- Model Architectures — 52 citations into it; #1,770 of 2,278 by trust here, #1,402 by citations
- Computational Theory and Mathematics — 41 citations into it; #10,023 of 12,182 by trust here, #3,117 by citations
- Information Systems — 39 citations into it; #6,292 of 8,771 by trust here, #2,912 by citations
- Program Analysis & Verification — 35 citations into it
Whom Markus Norman Rabe trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Ilya Sutskever
- Guillaume Lample
- Geoffrey E. Hinton
- Ashish Vaswani
- Yoshua Bengio
- Christian Szegedy
- Kaiyu Yang
- Jia Deng
- Alex Krizhevsky
Who trusts Markus Norman Rabe overall
- Tri Dao
- Yuhuai Wu
- Jesse Michael Han
- Stanislas Polu
- Hao Liu
- Wenda Li
- Kaiyu Yang
- Jason M. Rute
- Amey Agrawal
- Hugo Touvron
Papers from Markus Norman Rabe's perspective
Ordered by how strongly the researchers Markus Norman Rabe 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
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
Their papers
- Memorizing Transformers (2022) — 249 citations
- Temporal Logics for Hyperproperties (2013) — 329 citations
- Self-attention Does Not Need $O(n^2)$ Memory (2021) — 205 citations
- Autoformalization with Large Language Models (2022) — 324 citations
- HOList: An Environment for Machine Learning of Higher-Order Theorem Proving (extended version) (2019) — 59 citations
- Learning to Reason in Large Theories without Imitation (2019) — 45 citations
- Teaching Temporal Logics to Neural Networks (2020) — 79 citations
- Baldur: Whole-Proof Generation and Repair with Large Language Models (2023) — 195 citations
- LIME: Learning Inductive Bias for Primitives of Mathematical Reasoning (2021) — 69 citations
- Mathematical Reasoning via Self-supervised Skip-tree Training (2020) — 65 citations
- Language Modeling for Formal Mathematics (2020)
- HOList: An Environment for Machine Learning of Higher Order Logic Theorem Proving (2019) — 145 citations