kuleshov/deep-hybrid-models kuleshov/deep-hybrid-models

  • Stars
    star
    17
  • Rank 1,250,352 (Top 25 %)
  • Language
    Python
  • Created almost 7 years ago
  • Updated almost 7 years ago
Twitter logo Share LinkedIn logo Share Facebook logo Share
kuleshov/deep-hybrid-models
github

kuleshov

Reviews

There are no reviews yet. Be the first to send feedback to the community and the maintainers!

Repository Details

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

More Repositories

1

audio-super-res

Audio super resolution using neural networks
Python
1,139
star
2

teaching-material

Teaching materials for the machine learning and deep learning classes at Stanford and Cornell
Jupyter Notebook
1,096
star
3

cornell-cs5785-2020-applied-ml

Teaching materials for the applied machine learning course at Cornell Tech (online edition)
Jupyter Notebook
870
star
4

minillm

MiniLLM is a minimal system for running modern LLMs on consumer-grade GPUs
Python
842
star
5

cornell-cs5785-2023-applied-ml

Lecture materials for Cornell CS5785 Applied Machine Learning (Fall 2023)
Jupyter Notebook
169
star
6

tf-wgan

Wasserstein DCGAN in Tensorflow/Keras
Python
94
star
7

gwaskb

Machine-curated database of genetic disease and genome-wide association studies
Jupyter Notebook
55
star
8

tensor-factorization

Tensor Factorization via Matrix Factorization
MATLAB
33
star
9

cs228-notes

Lecture notes on probabilistic graphical modeling, based on Stanford CS228 (work in progress!)
CSS
30
star
10

online-learning

A few basic online learning algorithms
Python
25
star
11

deep-learning-models

Implementations of popular deep learning models in Theano+Lasagne
Python
24
star
12

architect

Scaffolding genomes using synthetic long read clouds
Python
20
star
13

neural-variational-inference

Neural variational inference and learning in undirected graphical models http://www.stanford.edu/~kuleshov/papers/nips2017.pdf
Python
17
star
14

generalized-rayleigh-quotient

Fast algorithms for sparse principal component analysis
MATLAB
16
star
15

ProbHap

Probabilistic single-individual haplotyping
Python
9
star
16

prism

Statistical phasing software for long read data
Python
5
star
17

convolutional-draw

Tensorflow implementation of Convolutional DRAW by Gregor et al. (2016)
Python
5
star
18

lens

Variant calling and haplotyping algorithm optimized for synthetic long reads
Python
2
star
19

nanoscope

Metagenomic analysis pipeline aimed at synthetic long reads
C
2
star
20

dotfiles

Shell
1
star
21

scripts

Various short scripts I wrote for my work
Python
1
star
22

pixelcnn-pp-experiments

Python
1
star