Statistical Learning
GRAND-SLAMIN' Interpretable Additive Modeling with Structural Constraints
It is desirable to restrict the number of components (i.e., encourage sparsity) for
Personalized Adapter for Large Meteorology Model on Devices: Towards Weather Foundation Models
Accurately modeling weather variation pattern from large amount of meteorological variables sequences is increasingly vital for providing efficient weather analysis support for disaster warning.
InfoPrompt: Information-Theoretic Soft Prompt Tuning for Natural Language Understanding Junda Wu1 Tong Y u 2 Rui Wang 3 Zhao Song
However, recent works reveal that it is non-trivial to find a proper initialization of the prompt tokens.
Deep Learning for Computing Convergence Rates of Markov Chains
Markovian models, estimating the rate of convergence to equilibrium is critical.
Hybrid Generative AI for De Novo Design of Co-Crystals with Enhanced Tabletability
Furthermore, we explore the potential of language models in generating co-crystals. Finally, we present numerous previously unknown co-crystals predicted by GEM-CODE and discuss its potential in accelerating drug development.
