Danijar Hafner danijar

## 2016-09-24T05-54-08-dqn-gather.yaml
algorithms:
- config:
  | frame_skip: 6
  | history: 6
  | replay_capacity: 5e4
  name: DQN
  train_steps: 200000
  type: DQN
envs:
- SimpleGather-v0

## 2016-06-10-char-rnn-sample.md

      
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                danijar
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              June 10, 2016 09:48
            
          
    Char-RNN Sample

Parameters

dataset = ArxivAbstracts(
    categories='stat.ML cs.NE cs.LG math.OC',
    keywords='neural network deep')
max_length = 50
sampling_temperature = 0.5

  
## bug_matplotlib_threading.py
import random
import time
import threading
import matplotlib.pyplot as plt


class Plot:

    def __init__(self):
        plt.ion()

## script_tfidf.py
import argparse
import collections
import re

TOKEN_REGEX = re.compile(r'[A-Za-z]+')
BLACKLIST = set([
    'pdf', 'and', 'the', 'proceedings', 'conference', 'ieee', 'for',
    'about', 'details', 'data', 'with', 'arxiv', 'preprint', 'advances'])

def tokenize(line):
	algorithms:
	- config:
	\| frame_skip: 6
	\| history: 6
	\| replay_capacity: 5e4
	name: DQN
	train_steps: 200000
	type: DQN
	envs:
	- SimpleGather-v0
	import random
	import time
	import threading
	import matplotlib.pyplot as plt


	class Plot:

	def __init__(self):
	plt.ion()
	import argparse
	import collections
	import re

	TOKEN_REGEX = re.compile(r'[A-Za-z]+')
	BLACKLIST = set([
	'pdf', 'and', 'the', 'proceedings', 'conference', 'ieee', 'for',
	'about', 'details', 'data', 'with', 'arxiv', 'preprint', 'advances'])

	def tokenize(line):