Unlike my posts, these notes are more informal and focused on personal understanding. They represent ongoing learning and may evolve as my understanding deepens.
Browse by Domain
Chemistry - Molecular design, representations, structure recognition, simulation, and LLM applications
- Molecular Design - De novo generation, property prediction, reaction prediction
- Molecular Representations - String notations, learned encoders, cross-modal models, name translation
- Optical Structure Recognition - Extracting molecular structures from images
- LLM Applications - General LLMs and VLMs adapted for chemical tasks
- Molecular Simulation - Molecular dynamics, force fields, 3D modeling, NNPs
- Datasets - Dataset cards
Machine Learning - Domain-agnostic ML methods, architectures, and theory
- Model Architectures - Architecture design, scaling, and inductive biases
- Generative Models - VAEs, diffusion models, and generative approaches
- Geometric Deep Learning - Equivariant networks and symmetry
Natural Language Processing - Language models, text understanding, and NLP methods
- Language Models - Architectures, pretraining, data scaling
Computational Biology - Protein folding, energy landscapes, and 3D point-set alignment algorithms
Research Methods - Meta-scientific frameworks and research methodologies