Caroline Trippel

Artificial Intelligence · 2020–2025

A researcher in the Science corpus: 4 papers; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 58 citations into it
• Information Systems — 46 citations into it

Whom Caroline Trippel trusts overall

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

1. Udit Gupta

Papers from Caroline Trippel's perspective

Ordered by how strongly the researchers Caroline Trippel 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. Attention is All you Need (Neural Information Processing Systems)
3. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
4. ImageNet: A large-scale hierarchical image database
5. Deep Neural Networks for YouTube Recommendations
6. DeepFM: A Factorization-Machine based Neural Network for CTR Prediction
7. Deep Learning Recommendation Model for Personalization and Recommendation Systems
8. Deep Interest Network for Click-Through Rate Prediction
9. In-datacenter performance analysis of a tensor processing unit
10. Neural Collaborative Filtering

Their papers

• VeriCoder: Enhancing LLM-Based RTL Code Generation through Functional Correctness Validation (2025)
• RecShard: statistical feature-based memory optimization for industry-scale neural recommendation (2022) — 81 citations
• RecSSD: near data processing for solid state drive based recommendation inference (2021) — 135 citations
• CPR: Understanding and Improving Failure Tolerant Training for Deep Learning Recommendation with Partial Recovery (2020) — 47 citations