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Deep Generative Models and Applications

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Deep Generative Models and Applications

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Topics in statistical physics of high-dimensional machine learning

Robust machine learning for neuroscientific inference

Few-shot Learning for Efficient and Effective Machine Learning Model Adaptation

Understanding generalization and robustness in modern deep learning

Mitigating Object Dependencies: Improving Point Cloud Self-Supervised Learning through Object Exchange

Residual-based attention in physics-informed neural networks

Robust NAS under adversarial training: benchmark, theory, and beyond

MaskCLR: Attention-Guided Contrastive Learning for Robust Action Representation Learning

Text-to-Microstructure Generation Using Generative Deep Learning

Learning Informative Health Indicators Through Unsupervised Contrastive Learning