Some presentations on machine learning papers from other authors.

Papers Presented on:

"The Autoencoding Variational Autoencoder" -> autoVAE.pdf

"GraphEDM: A Unified Framework for Machine Learning on Graphs" -> GraphEDM.pdf

"Graphite: Iterative Generative Modeling of Graphs" -> Graphite.pdf

"Bayesian Causal Structural Learning with Zero-Inflated Poisson Bayesian Networks" -> ZIPBN.pdf

"Application of Phylogenetic Networks in Evolutionary Studies" -> PhylogeneticNetworks.pdf

"Fully Bayesian analysis of RNA-seq counts for the detection of gene expression heterosis" -> FullyBayesRNA.pdf

"A hierarchical Bayesian model for single-cell clustering using RNA-sequencing data" -> BasClu.pdf "Amortized Monte Carlo Integration" -> AMCI.pdf

"Surrogate Likelihoods for Variational Annealed Importance Sampling" -> Surrogate_Likelihoods.pdf

Probabilstic Machine Learning: Advanced Topics - Variational Inference -> VI_Talk.pdf

Advanced Data Analysis from an Elementary Point of View (Part III: Causal Inference) -> Causal_Inference_Talk.pdf

deepST.pdf is a presentation about the early stages of my personal work with Graph Neural Networks and Spatial Transcriptomics.