1 code implementation • 20 Jul 2023 • Borja Rodríguez-Gálvez, Arno Blaas, Pau Rodríguez, Adam Goliński, Xavier Suau, Jason Ramapuram, Dan Busbridge, Luca Zappella
We consider a different lower bound on the MI consisting of an entropy and a reconstruction term (ER), and analyze the main MVSSL families through its lens.
1 code implementation • ICLR Workshop GTRL 2021 • Piotr Tempczyk, Rafał Michaluk, Łukasz Garncarek, Przemysław Spurek, Jacek Tabor, Adam Goliński
We attempt to address that challenge by proposing a novel approach to the problem: Local Intrinsic Dimension estimation using approximate Likelihood (LIDL).
1 code implementation • 30 Jan 2022 • Emilien Dupont, Hrushikesh Loya, Milad Alizadeh, Adam Goliński, Yee Whye Teh, Arnaud Doucet
Neural compression algorithms are typically based on autoencoders that require specialized encoder and decoder architectures for different data modalities.
no code implementations • pproximateinference AABI Symposium 2021 • Tim Reichelt, Adam Goliński, Luke Ong, Tom Rainforth
We show that the standard computational pipeline of probabilistic programming systems (PPSs) can be inefficient for estimating expectations and introduce the concept of expectation programming to address this.
1 code implementation • ICLR Workshop Neural_Compression 2021 • Emilien Dupont, Adam Goliński, Milad Alizadeh, Yee Whye Teh, Arnaud Doucet
We propose a new simple approach for image compression: instead of storing the RGB values for each pixel of an image, we store the weights of a neural network overfitted to the image.
1 code implementation • 18 Jul 2019 • Adam Goliński, Frank Wood, Tom Rainforth
At runtime, samples are produced separately from each amortized proposal, before being combined to an overall estimate of the expectation.