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[AISTATS 2025] Geometry-Aware Generative Autoencoders for Warped Riemannian Metric Learning and Generative Modeling on Data Manifolds
PyTorch Lightning + Hydra. A very user-friendly template for ML experimentation. ⚡🔥⚡
Transposition in PyTorch to Sklearn models such as Random Forest or SVM
Generating and Imputing Tabular Data via Diffusion and Flow XGBoost Models
R- package SLEMI presented in Jetka et al. "Information-theoretic analysis of multivariate single-cell signaling responses." PLoS computational biology (2019).
A minimal helper for ploting 3D scatter plots with plotly
a unified single-cell data integration framework by optimal transport
Tools to connect to and interact with the Mila cluster
reComBat package to correct batch effects
Official implementation of A* Networks
Geometry Regularized Autoencoders (GRAE) for large-scale visualization and manifold learning
Shuang Ni's home page.
a template for research group sites
PHATE (Potential of Heat-diffusion for Affinity-based Transition Embedding) is a tool for visualizing high dimensional data.