Dietmar Jannach
Information Systems · 2010–2020
A researcher in the Science corpus: 12 papers; trusts 198 researchers and is trusted by 37 researchers here, as inferred from the citation graph.
Subfields
- Information Systems — 210 citations into it; #673 of 8,771 by trust here, #594 by citations
- Artificial Intelligence — 165 citations into it; #6,527 of 35,345 by trust here, #8,077 by citations
- Management Science and Operations Research — 79 citations into it; #1,355 of 11,946 by trust here, #1,440 by citations
- Computer Vision and Pattern Recognition — 66 citations into it; #11,190 of 21,575 by trust here, #8,952 by citations
- Recommender Systems — 46 citations into it
- Signal Processing — 33 citations into it
- Marketing — 29 citations into it
- Natural Language Processing — 23 citations into it
Whom Dietmar Jannach trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Balázs Hidasi
- Steffen Rendle
- Yoshua Bengio
- Geoffrey E. Hinton
- Gediminas Adomavicius
- Sepp Hochreiter
- Alex Graves
- Paul Resnick
- Jonathan L. Herlocker
- Diederik P. Kingma
Who trusts Dietmar Jannach overall
- Malte Ludewig
- Shoujin Wang
- Jiaxi Tang
- Shuai Zhang
- Le Wu
- Ruihong Qiu
- Mozhgan Karimi
- Ziyang Wang
- Jiaxuan You
- Shu Wu
Papers from Dietmar Jannach's perspective
Ordered by how strongly the researchers Dietmar Jannach 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
- Long Short-Term Memory
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- Learning Multiple Layers of Features from Tiny Images
Their papers
- Are we really making much progress? A worrying analysis of recent neural recommendation approaches (2019) — 686 citations
- When Recurrent Neural Networks meet the Neighborhood for Session-Based Recommendation (2017) — 494 citations
- Sequence-Aware Recommender Systems (2018) — 565 citations
- Evaluation of session-based recommendation algorithms (2018) — 322 citations
- Beyond accuracy: evaluating recommender systems by coverage and serendipity (2010) — 761 citations
- News recommender systems - Survey and roads ahead (2018) — 326 citations
- Multistakeholder recommendation: Survey and research directions (2020) — 301 citations
- A Survey on Conversational Recommender Systems (2020) — 563 citations
- A systematic review and taxonomy of explanations in decision support and recommender systems (2017) — 384 citations
- Music Recommendation (2016)
- How should I explain? A comparison of different explanation types for recommender systems (2014) — 343 citations
- Recommender Systems: Introduction (2010) — 1,455 citations