Kevin Course

According to our database, Kevin Course authored at least 7 papers between 2020 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

Bending the Scaling Law Curve in Large-Scale Recommendation Systems.

Qin Ding, Kevin Course, Linjian Ma, Jianhui Sun, Ruochen Liu, Zhao Zhu, Chunxing Yin, Wei Li, Dai Li, Yu Shi, Xuan Cao, Ze Yang, Han Li, Xing Liu, Bi Xue, Hongwei Li, Rui Jian, Daisy Shi He, Jing Qian, Matt Ma, Qunshu Zhang, Rui Li

CoRR, February, 2026

Data-driven stochastic reduced-order modeling of parametrized dynamical systems.

Andrew F. Ilersich, Kevin Course, Prasanth B. Nair

CoRR, January, 2026

2025

Realizing Scaling Laws in Recommender Systems: A Foundation-Expert Paradigm for Hyperscale Model Deployment.

Dai Li, Kevin Course, Wei Li, Hongwei Li, Jie Hua, Yiqi Chen, Zhao Zhu, Rui Jian, Xuan Cao, Bi Xue, Yu Shi, Jing Qian, Kai Ren, Matt Ma, Qunshu Zhang, Rui Li

CoRR, August, 2025

Shifting Time: Time-series Forecasting with Khatri-Rao Neural Operators.

Srinath Dama, Kevin Course, Prasanth B. Nair

Proceedings of the Forty-second International Conference on Machine Learning, 2025

2023

State estimation of a physical system with unknown governing equations.

Kevin Course, Prasanth B. Nair

Nat., 2023

Amortized Reparametrization: Efficient and Scalable Variational Inference for Latent SDEs.

Kevin Course, Prasanth B. Nair

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2020

Weak Form Generalized Hamiltonian Learning.

Kevin Course, Trefor W. Evans, Prasanth B. Nair

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020