Yichao Lu

Research Scientist, Layer 6 AI

Joined

April 2018

Names

Yichao Lu

Emails

****@cs.toronto.edu (Confirmed)

****@layer6.ai (Confirmed)

Personal Links

Homepage

Google Scholar

Semantic Scholar

Career & Education History

Research Scientist

Layer 6 AI (layer6.ai)

2019 – Present

MS student

Department of Computer Science, University of Toronto (cs.toronto.edu)

2017 – 2019

Undergrad student

Fudan University (fudan.edu.cn)

2013 – 2017

Advisors, Relations & Conflicts

No relations added

Expertise

recommender systems

2013 – Present

Publications

Forecasting the future of artificial intelligence with machine learning-based link prediction in an exponentially growing knowledge network
Mario Krenn, Lorenzo Buffoni, Bruno C. Coutinho, Sagi Eppel, Jacob Gates Foster, Andrew Gritsevskiy, Harlin Lee, Yichao Lu, João P. Moutinho, Nima Sanjabi, Rishi Sonthalia, Ngoc Mai Tran, Francisco Valente, Yangxinyu Xie, Rose Yu, Michael Kopp
- Nat. Mac. Intell. 2023
- Readers: Everyone
Robust User Engagement Modeling With Transformers and Self Supervision
Yichao Lu, Maksims Volkovs
- RecSys Challenge 2023
- Readers: Everyone
Traffic4cast at NeurIPS 2022 - Predict Dynamics along Graph Edges from Sparse Node Data: Whole City Traffic and ETA from Stationary Vehicle Detectors
Moritz Neun, Christian Eichenberger, Henry Martin, Markus Spanring, Rahul Siripurapu, Daniel Springer, Leyan Deng, Chenwang Wu, Defu Lian, Min Zhou, Martin Lumiste, Andrei Ilie, Xinhua Wu, Cheng Lyu, Qing-Long Lu, Vishal Mahajan, Yichao Lu, Jiezhang Li, Junjun Li, Yue-Jiao Gong et al. (10 additional authors not shown)
- 2023 (modified: 21 Apr 2023)
- CoRR 2023
- Readers: Everyone
An Efficient Two-stage Gradient Boosting Framework for Short-term Traffic State Estimation
Yichao Lu
- 2023 (modified: 21 Apr 2023)
- CoRR 2023
- Readers: Everyone
Predicting Research Trends in Artificial Intelligence with Gradient Boosting Decision Trees and Time-aware Graph Neural Networks
Yichao Lu
- 2022 (modified: 21 Apr 2023)
- CoRR 2022
- Readers: Everyone
Traffic4cast at NeurIPS 2021 - Temporal and Spatial Few-Shot Transfer Learning in Gridded Geo-Spatial Processes
Christian Eichenberger, Moritz Neun, Henry Martin, Pedro Herruzo, Markus Spanring, Yichao Lu, Sungbin Choi, Vsevolod Konyakhin, Nina Lukashina, Aleksei Shpilman, Nina Wiedemann, Martin Raubal, Bo Wang, Hai L. Vu, Reza Mohajerpoor, Chen Cai, Inhi Kim, Luca Hermes, Andrew Melnik, Riza Velioglu et al. (17 additional authors not shown)
- 2022 (modified: 21 Apr 2023)
- CoRR 2022
- Readers: Everyone
Predicting the Future of AI with AI: High-quality link prediction in an exponentially growing knowledge network
Mario Krenn, Lorenzo Buffoni, Bruno Coutinho, Sagi Eppel, Jacob Gates Foster, Andrew Gritsevskiy, Harlin Lee, Yichao Lu, João P. Moutinho, Nima Sanjabi, Rishi Sonthalia, Ngoc Mai Tran, Francisco Valente, Yangxinyu Xie, Rose Yu, Michael Kopp
- 2022 (modified: 21 Apr 2023)
- CoRR 2022
- Readers: Everyone
Learning to Transfer for Traffic Forecasting via Multi-task Learning
Yichao Lu
- 2021 (modified: 15 Dec 2021)
- CoRR 2021
- Readers: Everyone
Context-aware Scene Graph Generation with Seq2Seq Transformers
Yichao Lu, Himanshu Rai, Jason Chang, Boris Knyazev, Guang Wei Yu, Shashank Shekhar, Graham W. Taylor, Maksims Volkovs
- 2021 (modified: 10 Nov 2022)
- ICCV 2021
- Readers: Everyone
Predicting Research Trends in Artificial Intelligence with Gradient Boosting Decision Trees and Time-aware Graph Neural Networks
Yichao Lu
- 2021 (modified: 21 Apr 2023)
- IEEE BigData 2021
- Readers: Everyone

View all 24 publications

Co-Authors

View all 97 co-authors