Gloria Fackelmann

Molecular Biology · 2021

A researcher in the Science corpus: 1 paper; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Molecular Biology — 21 citations into it
• Computational Biology & Bioinformatics — 16 citations into it
• Artificial Intelligence — 12 citations into it
• Representation & Self-Supervised Learning — 10 citations into it
• Graph Learning — 6 citations into it

Whom Gloria Fackelmann trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Maxat Kulmanov

Papers from Gloria Fackelmann's perspective

Ordered by how strongly the researchers Gloria Fackelmann trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Efficient Estimation of Word Representations in Vector Space
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
6. Semi-Supervised Classification with Graph Convolutional Networks (International Conference on Learning Representations)
7. Gradient-based learning applied to document recognition
8. Siamese Neural Networks for One-Shot Image Recognition
9. Attention is All you Need (Neural Information Processing Systems)
10. Long Short-Term Memory

Their papers

• Intrinsic-Extrinsic Convolution and Pooling for Learning on 3D Protein Structures (2021) — 124 citations