HarshTrivedi

import torch
from torch import LongTensor
from torch.nn import Embedding, LSTM
from torch.autograd import Variable
from torch.nn.utils.rnn import pack_padded_sequence, pad_packed_sequence

## We want to run LSTM on a batch of 3 character sequences ['long_str', 'tiny', 'medium']
#
#     Step 1: Construct Vocabulary
#     Step 2: Load indexed data (list of instances, where each instance is list of character indices)

jph00

rspeer

tboggs

robschmuecker

This example pulls together various examples of work with trees in D3.js.

The panning functionality can certainly be improved in my opinion and I would be thrilled to see better solutions contributed.

One can do all manner of housekeeping or server related calls on the drop event to manage a remote tree dataset for example.

Dragging can be performed on any node other than root (flare). Dropping can be done on any node.

Panning can either be done by dragging an empty part of the SVG around or dragging a node towards an edge.

larsmans

"""
Three ways of computing the Hellinger distance between two discrete
probability distributions using NumPy and SciPy.
"""

import numpy as np
from scipy.linalg import norm
from scipy.spatial.distance import euclidean

MohamedAlaa

tmux shortcuts & cheatsheet

start new:

tmux

start new with session name:

tmux new -s myname

shhong

#!/usr/bin/env python

"""
nsb_entropy.py

June, 2011 written by Sungho Hong, Computational Neuroscience Unit, Okinawa Institute of
Science and Technology
May, 2019 updated to Python 3 by Charlie Strauss, Los Alamos National Lab

This script is a python version of Mathematica functions by Christian Mendl