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Kyunghyun Cho

Showing results (1-10 of 42) with videos related to

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Journal of Chemical Information and Modeling|July 18, 2018
Conditional Molecular Design with Deep Generative ModelsSeokho Kang, Kyunghyun Cho
Neural Computation|November 15, 2012
Enhanced gradient for training restricted Boltzmann machinesKyunghyun Cho, Tapani Raiko, Alexander Ilin
Neural Networks : the Official Journal of the International Neural Network Society|October 17, 2014
Measuring the usefulness of hidden units in Boltzmann machines with mutual informationMathias Berglund, Tapani Raiko, Kyunghyun Cho
Bioinformatics (Oxford, England)|August 23, 2022
NetTIME: a multitask and base-pair resolution framework for improved transcription factor binding site predictionRen Yi, Kyunghyun Cho, Richard Bonneau
Neural Computation|January 31, 2018
Dynamic Neural Turing Machine with Continuous and Discrete Addressing SchemesCaglar Gulcehre, Sarath Chandar, Kyunghyun Cho, et al.
Scientific Reports|January 2, 2020
Molecular Geometry Prediction using a Deep Generative Graph Neural NetworkElman Mansimov, Omar Mahmood, Seokho Kang, et al.
Bioinformatics (Oxford, England)|February 12, 2021
NetQuilt: deep multispecies network-based protein function prediction using homology-informed network similarityMeet Barot, Vladimir Gligorijević, Kyunghyun Cho, et al.
Nature Communications|May 27, 2021
Masked graph modeling for molecule generationOmar Mahmood, Elman Mansimov, Richard Bonneau, et al.
Neural Networks : the Official Journal of the International Neural Network Society|October 9, 2014
Two-layer contractive encodings for learning stable nonlinear featuresHannes Schulz, Kyunghyun Cho, Tapani Raiko, et al.
Genome Biology|April 8, 2024
PMF-GRN: a variational inference approach to single-cell gene regulatory network inference using probabilistic matrix factorizationClaudia Skok Gibbs, Omar Mahmood, Richard Bonneau, et al.
Pageof 5

Showing results (1-10 of 42) with videos related to

Sort By:
Pageof 5
Journal of Chemical Information and Modeling|July 18, 2018
Conditional Molecular Design with Deep Generative ModelsSeokho Kang, Kyunghyun Cho
Neural Computation|November 15, 2012
Enhanced gradient for training restricted Boltzmann machinesKyunghyun Cho, Tapani Raiko, Alexander Ilin
Neural Networks : the Official Journal of the International Neural Network Society|October 17, 2014
Measuring the usefulness of hidden units in Boltzmann machines with mutual informationMathias Berglund, Tapani Raiko, Kyunghyun Cho
Bioinformatics (Oxford, England)|August 23, 2022
NetTIME: a multitask and base-pair resolution framework for improved transcription factor binding site predictionRen Yi, Kyunghyun Cho, Richard Bonneau
Neural Computation|January 31, 2018
Dynamic Neural Turing Machine with Continuous and Discrete Addressing SchemesCaglar Gulcehre, Sarath Chandar, Kyunghyun Cho, et al.
Scientific Reports|January 2, 2020
Molecular Geometry Prediction using a Deep Generative Graph Neural NetworkElman Mansimov, Omar Mahmood, Seokho Kang, et al.
Bioinformatics (Oxford, England)|February 12, 2021
NetQuilt: deep multispecies network-based protein function prediction using homology-informed network similarityMeet Barot, Vladimir Gligorijević, Kyunghyun Cho, et al.
Nature Communications|May 27, 2021
Masked graph modeling for molecule generationOmar Mahmood, Elman Mansimov, Richard Bonneau, et al.
Neural Networks : the Official Journal of the International Neural Network Society|October 9, 2014
Two-layer contractive encodings for learning stable nonlinear featuresHannes Schulz, Kyunghyun Cho, Tapani Raiko, et al.
Genome Biology|April 8, 2024
PMF-GRN: a variational inference approach to single-cell gene regulatory network inference using probabilistic matrix factorizationClaudia Skok Gibbs, Omar Mahmood, Richard Bonneau, et al.
Pageof 5