stats
Efficient Gaussian Process Computation
I’ll try to give examples of efficient gaussian process computation here, like the vec trick (Kronecker product trick), efficient toeliptz and circulant matrix computations, RTS smoothing and Kalman filtering using state space representations, and so on.
Gaussian Process Speech Synthesis (Draft)
Very untidy first working draft of the idea mentioned on the efficient computation page. Here, I fit a spectral mixture to some audio data to build a “generative model” for audio. I’ll implement efficient sampling later, and I’ll replace the arbitrary way this is trained with an LSTM-RNN to go straight from text/spectrograms to waveforms.
Random Projects
Random Projects
Gaussian Process Middle C
First of my experiments on audio modelling using gaussian processes. Here, I construct a GP that, when sampled, plays middle c the way a grand piano would.
An Ising-Like Model
… using Stan & HMC
Sparse Gaussian Process Examples
A Minimal Working Example
Random Stuff
Random Stuff
Stochastic Bernoulli Probabilities
Consider:
Musings on Statistics
Musings on Statistics
Measures & Defining Probability
Probability & Sigma Algebras
Gaussian Processes
Introduction
The Log-Likelihood & Dimensionality
Introduction
Non-Monotonic Transforms
Exact Densities for Non-Monotonic Transformations (draft)
R
Gaussian Process Middle C
First of my experiments on audio modelling using gaussian processes. Here, I construct a GP that, when sampled, plays middle c the way a grand piano would.
An Ising-Like Model
… using Stan & HMC
Sparse Gaussian Process Examples
A Minimal Working Example
Gaussian Processes
Introduction
Non-Monotonic Transforms
Exact Densities for Non-Monotonic Transformations (draft)
python
Efficient Gaussian Process Computation
I’ll try to give examples of efficient gaussian process computation here, like the vec trick (Kronecker product trick), efficient toeliptz and circulant matrix computations, RTS smoothing and Kalman filtering using state space representations, and so on.
Gaussian Process Speech Synthesis (Draft)
Very untidy first working draft of the idea mentioned on the efficient computation page. Here, I fit a spectral mixture to some audio data to build a “generative model” for audio. I’ll implement efficient sampling later, and I’ll replace the arbitrary way this is trained with an LSTM-RNN to go straight from text/spectrograms to waveforms.
Gaussian Processes
Introduction
c
Efficient Gaussian Process Computation
I’ll try to give examples of efficient gaussian process computation here, like the vec trick (Kronecker product trick), efficient toeliptz and circulant matrix computations, RTS smoothing and Kalman filtering using state space representations, and so on.