Florian Matthes
Molecular Biology · 2017–2021
A researcher in the Science corpus: 4 papers; trusts 48 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Molecular Biology — 129 citations into it
- Computational Biology & Bioinformatics — 58 citations into it
- Artificial Intelligence — 46 citations into it
- Natural Language Processing — 37 citations into it
- Materials Chemistry — 31 citations into it
- Genetics — 15 citations into it
- Representation & Self-Supervised Learning — 15 citations into it
- Model Architectures — 13 citations into it
Whom Florian Matthes trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Burkhard Rost
- Christopher Sander
- Diederik P. Kingma
- Geoffrey E. Hinton
- Avner Schlessinger
- Ehud Reiter
- Sebastian Briesemeister
- Tomas Mikolov
- Sepp Hochreiter
- Sergey Ioffe
Papers from Florian Matthes's perspective
Ordered by how strongly the researchers Florian Matthes trusts endorse each paper. Same corpus, a different order for every researcher.
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- 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
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Gradient-based learning applied to document recognition
- Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- GloVe: Global Vectors for Word Representation
Their papers
- Modeling aspects of the language of life through transfer-learning protein sequences (2019) — 548 citations
- Modeling the language of life – Deep Learning Protein Sequences (2019) — 48 citations
- CodeTrans: Towards Cracking the Language of Silicone's Code Through Self-Supervised Deep Learning and High Performance Computing (2021) — 85 citations
- Evaluating Natural Language Understanding Services for Conversational Question Answering Systems (2017) — 192 citations