Chemical Reaction Prediction: Molecular Transformer

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Explores the impact of Deep learning on Digital Humanities, focusing on non conceptual knowledge systems and recent advancements in AI.

Transformer Architecture: The X Gomega

Delves into the Transformer architecture, self-attention, and training strategies for machine translation and image recognition.

Machine Translation: Sequence-to-Sequence and Attention

Explores the advancements in Machine Translation, focusing on Sequence-to-Sequence models and Attention mechanisms.

Sequence to Sequence Models: Overview and Attention Mechanisms

Explores sequence to sequence models, attention mechanisms, and their role in addressing model limitations and improving interpretability.

Coreference Resolution

Covers coreference resolution, models, applications, challenges, and advancements in natural language processing.

Multilingual NLP: Challenges and Innovations

Covers the importance of multilingual NLP and the challenges in scaling language models.

Trajectory Forecasting in Autonomous Vehicles

Explores trajectory forecasting in autonomous vehicles, focusing on deep learning models for predicting human trajectories in socially-aware transportation scenarios.

Transformers: Unifying Machine Learning Communities

Covers the role of Transformers in unifying various machine learning fields.

Neural Networks Optimization

Explores neural networks optimization, including backpropagation, batch normalization, weight initialization, and hyperparameter search strategies.

Deep Learning for NLP

Explores deep learning for NLP, covering word embeddings, context representations, learning techniques, and challenges like vanishing gradients and ethical considerations.