Model-free inference of diffusion networks using RKHS embeddings
Sign Up to like & getrecommendations! Published in 2018 at "Data Mining and Knowledge Discovery"
DOI: 10.1007/s10618-018-00611-1
Abstract: We revisit in this paper the problem of inferring a diffusion network from information cascades. In our study, we make no assumptions on the underlying diffusion model, in this way obtaining a generic method with… read more here.
Keywords: networks using; diffusion; inference diffusion; free inference ... See more keywords
Alignment-free inference of hierarchical and reticulate phylogenomic relationships
Sign Up to like & getrecommendations! Published in 2019 at "Briefings in Bioinformatics"
DOI: 10.1093/bib/bbx067
Abstract: Abstract We are amidst an ongoing flood of sequence data arising from the application of high-throughput technologies, and a concomitant fundamental revision in our understanding of how genomes evolve individually and within the biosphere. Workflows… read more here.
Keywords: inference hierarchical; hierarchical reticulate; free inference; alignment free ... See more keywords
pyABC: distributed, likelihood‐free inference
Sign Up to like & getrecommendations! Published in 2018 at "Bioinformatics"
DOI: 10.1093/bioinformatics/bty361
Abstract: Summary: Likelihood‐free methods are often required for inference in systems biology. While approximate Bayesian computation (ABC) provides a theoretical solution, its practical application has often been challenging due to its high computational demands. To scale… read more here.
Keywords: pyabc distributed; likelihood free; abc smc; free inference ... See more keywords
Massive optimal data compression and density estimation for scalable, likelihood-free inference in cosmology
Sign Up to like & getrecommendations! Published in 2018 at "Monthly Notices of the Royal Astronomical Society"
DOI: 10.1093/mnras/sty819
Abstract: Many statistical models in cosmology can be simulated forwards but have intractable likelihood functions. Likelihood-free inference methods allow us to perform Bayesian inference from these models using only forward simulations, free from any likelihood assumptions… read more here.
Keywords: likelihood free; cosmology; free inference; data compression ... See more keywords
Sum of the masses of the Milky Way and M31: A likelihood-free inference approach
Sign Up to like & getrecommendations! Published in 2021 at "Physical Review D"
DOI: 10.1103/physrevd.103.023009
Abstract: We use density estimation likelihood-free inference, $\mathrm{\ensuremath{\Lambda}}$ cold dark matter simulations of $\ensuremath{\sim}2M$ galaxy pairs, and data from Gaia and the Hubble Space Telescope to infer the sum of the masses of the Milky Way… read more here.
Keywords: free inference; sum masses; likelihood free; masses milky ... See more keywords
Search-free Inference Acceleration for Sparse Convolutional Neural Networks
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems"
DOI: 10.1109/tcad.2021.3102191
Abstract: Sparse convolution neural networks (CNNs) are promising in reducing both memory usage and computational complexity while still preserving high inference accuracy. State-of-the-art sparse CNN accelerators can deliver high throughput by skipping zero weights and/or activations.… read more here.
Keywords: neural networks; sparse; free inference; search free ... See more keywords