FWIW I didn't have a very good experience when working with
> convolutional (shouldn't it be that?) NMF. Why no use an
> autoencoder approach?
Thanks for the suggestion. Exploring a few different paradigms at the
moment -
Best
Dan
> Andy
>
>
> On 04/09/2015 08:20 AM,
.ie/1375/1/getPDF2.pdf
Thanks
Dan
--
Dan Stowell
EPSRC Research Fellow
Centre for Digital Music
Queen Mary, University of London
Mile End Road, London E1 4NS
http://www.mcld.co.uk/research/
--
BPM Camp - Free Virtual W
signals directly from within Python.
Best
Dan
--
Dan Stowell
Postdoctoral Research Assistant
Centre for Digital Music
Queen Mary, University of London
Mile End Road, London E1 4NS
http://www.elec.qmul.ac.uk/digitalmusic/people/dans.htm
http://www.mcld.co.uk
info/aasp-challenge>.
Best wishes,
The organisers -- Dimitrios Giannoulis (QMUL), Emmanouil Benetos
(CityU/QMUL), Dan Stowell (QMUL), Mathias Rossignol (IRCAM), Mathieu
Lagrange (IRCAM) and Mark D. Plumbley (QMUL)
--
M
On 31/10/12 16:09, bthirion wrote:
> On 10/31/2012 04:50 PM, Dan Stowell wrote:
>> Hi all,
>>
>> I'm still getting odd results using mixture.GMM depending on data
>> scaling. In the following code example, I change the overall scaling but
>> I do NOT change
27;, n_components=10)
7094.87886779
GMM(cvtype='diag', n_components=10)
-14681.566456
GMM(cvtype='diag', n_components=10)
-37576.4496656
In principle, I don't think the overall data scaling should matter, but
maybe there's an implementation issue I'm overlooking?
Th
On 02/10/12 13:58, Alexandre Passos wrote:
> On Tue, Oct 2, 2012 at 7:48 AM, Dan Stowell
> wrote:
>>
>> Hi all,
>>
>> I'm using the GMM class as part of a larger system, and something is
>> misbehaving. Can someone confirm please: the results of u
as a range
0-1, that difference shouldn't have much bearing?
Thanks
Dan
--
Dan Stowell
Postdoctoral Research Assistant
Centre for Digital Music
Queen Mary, University of London
Mile End Road, London E1 4NS
http://www.elec.qmul.ac.uk/digitalmusic/people/dans.htm
http:/
Hi -
I'm looking for Python implementations of the PHD filter (Probability
Hypothesis Density filter). The acronym makes web search quite hard!
It's a technique for multi-object tracking in noisy observations.
Aware of any python code for PHD filtering, please?
Thanks
Dan
--
D
mplied by the prior on the
coefficients.
* Given the above, is it correct to include log(clf.alpha) in the
probability calculation?
Thanks for any advice you can give -
Dan
--
Dan Stowell
Postdoctoral Research Assistant
Centre for Digital Music
Queen Mary, University of London
Mile End Road,
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