3D Steerable CNNs: Learning Rotationally Equivariant Features in Volumetric Data
Weiler et al.'s NeurIPS 2018 paper introducing SE(3)-equivariant CNNs for volumetric data using group theory and …...
Weiler et al.'s NeurIPS 2018 paper introducing SE(3)-equivariant CNNs for volumetric data using group theory and …...
Enhanced TABME benchmark for page stream segmentation, creating TABME++, showing fine-tuned decoder-based LLMs …...
VAE tutorial using modern PyTorch: torch.distributions, optimization techniques, numerical stability, and implementation …
Supervised learning reveals hidden eigenvalue patterns that clustering missed, testing k-NN and logistic regression on …
Clustering analysis reveals why Coulomb matrix eigenvalues struggle with larger alkanes, using Dunn Index and silhouette …
Explore molecular shape recognition using Coulomb matrix eigenvalues. Analysis of alkane isomers from data generation to …
Testing ML classification of congressional bills by policy area. Comparing Naive Bayes, Logistic Regression, and XGBoost …
Learn how Coulomb matrices encode 3D molecular structure for machine learning—from basic theory to Python implementation …
Data science project scraping 47,000+ congressional bills, analyzing legislative patterns, and building ML models …...
Investigation into EigenNoise, a data-free initialization scheme for word vectors that approaches pre-trained model …...
Campos & Ji's method for converting 2D molecular images to SMILES strings using Transformers and SELFIES representation....
Undergraduate thesis exploring representation learning for social media text and developing tools for cross-platform …