JackKelly neuralnilm_prototype issues

JackKelly / neuralnilm_prototype

MIT License

51 stars 22 forks source link

issues

Newest

Newest Most commented Recently updated Oldest Least commented Least recently updated

give the net two inputs: raw power and fdiff

#48 JackKelly opened 9 years ago
0
Truncated back prop

#47 JackKelly closed 9 years ago
1
Gradient clipping

#46 JackKelly opened 9 years ago
0
When target is single appliance, validation data must include that appliance!

#45 JackKelly closed 9 years ago
1
Automate running multiple models

#44 JackKelly opened 9 years ago
0
Deep Latent Gaussian Models (DLGMs)

#43 JackKelly opened 9 years ago
0
Fix NaNs during training on 5-appliances

#42 JackKelly opened 9 years ago
0
Should I take the average of the training costs for plotting?

#41 JackKelly closed 9 years ago
1
Validation data should use different activations

#40 JackKelly opened 9 years ago
0
Automatic architecture search

#39 JackKelly opened 9 years ago
0
Try quantising input data OR using linspace to init weights

#38 JackKelly opened 9 years ago
0
More realistic data

#37 JackKelly opened 9 years ago
1
Pipeline for processing inputs and outputs

#36 JackKelly opened 9 years ago
0
Clockwork RNNs

#35 JackKelly opened 9 years ago
0
Build awesome disag algo into a web service

#34 JackKelly opened 9 years ago
0
train net on many appliances and then extract the ‘knowledge’ for a single appliance?

#33 JackKelly opened 9 years ago
0
Dealing with missing samples and different sample rates

#32 JackKelly opened 9 years ago
0
force the outputs to sum to no more than the aggregate power demand at each time slice

#31 JackKelly opened 9 years ago
0
MultiModel disaggregation

#30 JackKelly opened 9 years ago
0
Ensemble

#29 JackKelly opened 9 years ago
0
Mixture density network

#28 JackKelly opened 9 years ago
0
Use two networks: one outputs boolean for if the appliance is on or off

#27 JackKelly opened 9 years ago
0
Pre train on unlabelled data (e.g from xively)

#26 JackKelly opened 9 years ago
0
one network per appliance (multiple experts) vs one network for all classes of appliances

#25 JackKelly opened 9 years ago
0
'Skip' connections

#24 JackKelly opened 9 years ago
0
Output both power demand and classification

#23 JackKelly opened 9 years ago
0
Try getting net to map just from fdiff to quantized fdiff

#22 JackKelly opened 9 years ago
0
Comparisons for paper

#21 JackKelly opened 9 years ago
0
curriculum training

#20 JackKelly opened 9 years ago
0
Inputs and representation

#19 JackKelly opened 9 years ago
0
Save and load learnt params to disk

#18 JackKelly opened 9 years ago
0
More FF layers at the top of the network

#17 JackKelly opened 9 years ago
0
NILM formulated as a sequence-to-sequence problem where the output is Fridge=[12:30-12:50, etc]

#16 JackKelly opened 9 years ago
0
Visualise what each neuron is interested in

#15 JackKelly opened 9 years ago
0
Regularization

#14 JackKelly opened 9 years ago
0
Target representation

#13 JackKelly opened 9 years ago
0
NILM Metrics

#12 JackKelly opened 9 years ago
0
move Source and RealApplianceSource classes into NILMTK

#11 JackKelly opened 9 years ago
0
logging

#10 JackKelly opened 9 years ago
0
modify cost to severely penalise during training if the sum of the estimates is greater than the input

#9 JackKelly opened 9 years ago
0
single-directional HSLSTM

#8 JackKelly opened 9 years ago
0
Train from multiple datasets at different sample rates

#7 JackKelly opened 9 years ago
0
Batch normalisation

#6 JackKelly opened 9 years ago
0
Whole chapter could be on unsupervised training of auto encoders

#5 JackKelly opened 9 years ago
0
Layer wise pre-training

#4 JackKelly opened 9 years ago
0
1D convnet input

#3 JackKelly opened 9 years ago
0
Centre input array when using pad_input

#2 JackKelly closed 9 years ago
0
Check Source inits array to zeros in gen_data

#1 JackKelly closed 9 years ago
0