Volodymyr Kuleshov

audio-super-res. Audio super resolution using neural networks

cornell-cs5785-2020-applied-ml. Teaching materials for the applied machine learning course at Cornell Tech (online edition)

teaching-material. Teaching materials for the machine learning and deep learning classes at Stanford and Cornell

minillm. MiniLLM is a minimal system for running modern LLMs on consumer-grade GPUs

cornell-cs5785-2025-applied-ml. Lecture materials for Cornell CS5785 Applied Machine Learning (Fall 2024)

tf-wgan. Wasserstein DCGAN in Tensorflow/Keras

gwaskb. Machine-curated database of genetic disease and genome-wide association studies

tensor-factorization. Tensor Factorization via Matrix Factorization

cs228-notes. Lecture notes on probabilistic graphical modeling, based on Stanford CS228 (work in progress!)

deep-learning-models. Implementations of popular deep learning models in Theano+Lasagne

online-learning. A few basic online learning algorithms

architect. Scaffolding genomes using synthetic long read clouds

generalized-rayleigh-quotient. Fast algorithms for sparse principal component analysis

neural-variational-inference. Neural variational inference and learning in undirected graphical models http://www.stanford.edu/~kuleshov/papers/nips2017.pdf

deep-hybrid-models. Deep hybrid models: bridging discriminative and generative approaches https://cs.stanford.edu/~ermon/papers/uai2017_cr.pdf

ProbHap. Probabilistic single-individual haplotyping

char-mdlm. Character-level masked diffusion language models

prism. Statistical phasing software for long read data

convolutional-draw. Tensorflow implementation of Convolutional DRAW by Gregor et al. (2016)

nanoscope. Metagenomic analysis pipeline aimed at synthetic long reads

simple-masked-diffusion-language-models. Python

lens. Variant calling and haplotyping algorithm optimized for synthetic long reads

scripts. Various short scripts I wrote for my work

diffusion-llm. Simplified Masked Diffusion Language Model

dotfiles. Shell

pixelcnn-pp-experiments. Python

multivariate-deep-learning. Jupyter Notebook