5 papers
Rethinking Sparse Mixture of Experts from a Unified Perspective
Giang Do, Hung Le, Truyen Tran
Sparse Mixture of Experts (SMoE) models scale the capacity of models while maintaining constant computational overhead. SMoE methods fall into two categories: Token Choice, which r…
On the Role of Discrete Representation in Sparse Mixture of Experts
Giang Do, Kha Pham, Hung Le +1
Sparse mixture of experts (SMoE) is an effective solution for scaling up model capacity without increasing the computational costs. A crucial component of SMoE is the router, respo…
S2MoE: Robust Sparse Mixture of Experts via Stochastic Learning
Giang Do, Hung Le, Truyen Tran
Sparse Mixture of Experts (SMoE) enables efficient training of large language models by routing input tokens to a select number of experts. However, training SMoE remains challengi…
Machine Learning-Integrated Modeling of Thermal Properties and Relaxation Dynamics in Metallic Glasses
Ngo T. Que, Anh D. Phan, Truyen Tran +3
Metallic glasses are a promising class of materials celebrated for their exceptional thermal and mechanical properties. However, accurately predicting and understanding the melting…
MP-PINN: A Multi-Phase Physics-Informed Neural Network for Epidemic Forecasting
Thang Nguyen, Dung Nguyen, Kha Pham +1
Forecasting temporal processes such as virus spreading in epidemics often requires more than just observed time-series data, especially at the beginning of a wave when data is limi…