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Found 5 papers, 3 papers with code
Empirical Evidence for the Fragment level Understanding on Drug Molecular Structure of LLMs
AI for drug discovery has been a research hotspot in recent years, and SMILES-based language models has been increasingly applied in drug molecular design.
De novo Drug Design using Reinforcement Learning with Multiple GPT Agents
A central challenge in this field is to generate molecules with specific properties while also producing a wide range of diverse candidates.
Randomized Sharpness-Aware Training for Boosting Computational Efficiency in Deep Learning
Optimizers in RST would perform a Bernoulli trial at each iteration to choose randomly from base algorithms (SGD) and sharpness-aware algorithms (SAM) with a probability arranged by a predefined scheduling function.
Penalizing Gradient Norm for Efficiently Improving Generalization in Deep Learning
In this paper, we propose an effective method to improve the model generalization by additionally penalizing the gradient norm of loss function during optimization.
Role Taxonomy of Units in Deep Neural Networks
Identifying the role of network units in deep neural networks (DNNs) is critical in many aspects including giving understandings on the mechanisms of DNNs and building basic connections between deep learning and neuroscience.
