Marcin J. Skwark
Molecular Biology · 2014–2024
A researcher in the Science corpus: 5 papers; trusts 29 researchers and is trusted by 7 researchers here, as inferred from the citation graph.
Subfields
- Molecular Biology — 122 citations into it; #4,752 of 17,773 by trust here, #7,911 by citations
- Computational Biology & Bioinformatics — 74 citations into it; #351 of 660 by trust here, #484 by citations
- Artificial Intelligence — 25 citations into it
- Materials Chemistry — 24 citations into it; #4,342 of 11,513 by trust here, #7,644 by citations
- Computational Theory and Mathematics — 5 citations into it
Whom Marcin J. Skwark trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- David C. Jones
- Yang Zhang
- Zhiyong Wang
- Martin Weigt
- Lukas Burger
- Pietro Di Lena
- John L. Klepeis
- Gianluca Pollastri
- Faruck Morcos
- Pierre Baldi
Who trusts Marcin J. Skwark overall
- Mirco Michel
- David Ménendez Hurtado
- Badri Adhikari
- H. Szurmant
- Arne Elofsson
- Susann Vorberg
- Mu Gao
- Sheng Wang
- Martin Weigt
- Stefan Seemayer
Papers from Marcin J. Skwark's perspective
Ordered by how strongly the researchers Marcin J. Skwark trusts endorse each paper. Same corpus, a different order for every researcher.
- Attention is All you Need (Neural Information Processing Systems)
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Learning Multiple Layers of Features from Tiny Images
- Going deeper with convolutions
Their papers
- Improved Contact Predictions Using the Recognition of Protein Like Contact Patterns (2014) — 163 citations
- Predicting accurate contacts in thousands of Pfam domain families using PconsC3 (2017) — 42 citations
- The Nucleotide Transformer: Building and Evaluating Robust Foundation Models for Human Genomics (2024) — 552 citations
- Early computational detection of potential high-risk SARS-CoV-2 variants (2021) — 41 citations
- Accurate contact predictions for thousands of protein families using PconsC3 (2016) — 4 citations