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Transformer Models for Vision

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Transformer Models for Vision

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Probabilistic methods for neural combinatorial optimization

Improving Generalization of Pretrained Language Models

Fundamental Limits in Statistical Learning Problems: Block Models and Neural Networks

Multienzyme deep learning models improve peptide de novo sequencing by mass spectrometry proteomics

Interpretable Representation Learning and Evaluation for Abstractive Summarization

Confidence Matters: Applications to Semantic Segmentation

Fixing the problems of deep neural networks will require better training data and learning algorithms

Dense Image-based Predictions for Comics Analysis

Data-driven approaches for non-invasive cuffless blood pressure monitoring

4M: Massively Multimodal Masked Modeling