KyleOng

{
  "_start": 2019,
  "_end": 2021,
  "_citation": null,
  "_mdate": 1625056932.691998,
  "_json": {
    "abstract-citations-response": {
      "h-index": "1",
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KyleOng

from typing import Union

import numpy as np
import torch
from torch.utils.data import Dataset, DataLoader
from scipy.sparse import (random, 
                          coo_matrix,
                          csr_matrix, 
                          vstack)
from tqdm import tqdm

KyleOng

library(ggplot2)

gg.mixEM <- function(EM) {
    require(ggplot2)
    x       <- with(EM,seq(min(x)-1,max(x)+1,len=1000))
    pars    <- with(EM,data.frame(comp=colnames(posterior), mu, sigma,lambda))
    em.df   <- data.frame(x=rep(x,each=nrow(pars)),pars)
    em.df$y <- with(em.df,lambda*dnorm(x,mean=mu,sd=sigma))
    ggplot(data.frame(x=EM$x),aes(x,y=..density..)) + 
        geom_histogram(fill=NA,color="black",bins=41)+