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Architecture of the human regulatory network derived from ENCODE data

Nature (London), 2012-09, Vol.489 (7414), p.91-100

2012

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Rethinking Zero-Shot Learning: A Conditional Visual Classification Perspective

2019 IEEE/CVF International Conference on Computer Vision (ICCV), 2019, p.3582-3591

2019

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Systematic exploration of essential yeast gene function with temperature-sensitive mutants

Nature biotechnology, 2011-04, Vol.29 (4), p.361-367

2011

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TIP: A probabilistic method for identifying transcription factor target genes from ChIP-seq binding profiles

Bioinformatics, 2011-12, Vol.27 (23), p.3221-3227

2011

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Understanding transcriptional regulation by integrative analysis of transcription factor binding data

Genome research, 2012-09, Vol.22 (9), p.1658

2012

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Gene expression variability within and between human populations and implications toward disease susceptibility

PLoS computational biology, 2010-08, Vol.6 (8), p.e1000910

2010

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On TCR binding predictors failing to generalize to unseen peptides

Frontiers in immunology, 2022-10, Vol.13, p.1014256-1014256

2022

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High-order neural networks and kernel methods for peptide-MHC binding prediction

Bioinformatics (Oxford, England), 2015-11, Vol.31 (22), p.3600-3607

2015

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AE-StyleGAN: Improved Training of Style-Based Auto-Encoders

2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2022, p.955-964

2022

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Ranking-Based Convolutional Neural Network Models for Peptide-MHC Class I Binding Prediction

Frontiers in molecular biosciences, 2021-05, Vol.8, p.634836-634836

2021

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Accelerating deep neural network training with inconsistent stochastic gradient descent

Neural networks, 2017-09, Vol.93, p.219-229

2017

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Exploiting the determinants of stochastic gene expression in Saccharomyces cerevisiae for genome-wide prediction of expression noise

Proceedings of the National Academy of Sciences - PNAS, 2010-06, Vol.107 (23), p.10472-10477

2010

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Parametric t-Distributed Stochastic Exemplar-Centered Embedding

Machine Learning and Knowledge Discovery in Databases, p.477-493

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Model-based autoencoders for imputing discrete single-cell RNA-seq data

Methods (San Diego, Calif.), 2021-08, Vol.192, p.112-119

2021

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Fully convolutional structured LSTM networks for joint 4D medical image segmentation

2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018), 2018, p.1104-1108

2018

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S3VAE: Self-Supervised Sequential VAE for Representation Disentanglement and Data Generation

2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020, p.6537-6546

2020

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Impeller: a path-based heterogeneous graph learning method for spatial transcriptomic data imputation

Bioinformatics (Oxford, England), 2024-06, Vol.40 (6)

2024

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StyleT2I: Toward Compositional and High-Fidelity Text-to-Image Synthesis

2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022, p.18176-18186

2022

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Conditional Image-to-Video Generation with Latent Flow Diffusion Models

2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023, p.18444-18455

2023

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DECODE: a Deep-learning framework for Condensing enhancers and refining boundaries with large-scale functional assays

Bioinformatics, 2021-07, Vol.37 (Supplement_1), p.i280-i288

2021

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Attentive Variational Information Bottleneck for TCR–peptide interaction prediction

Bioinformatics (Oxford, England), 2023-01, Vol.39 (1)

2023

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DECODE: a De ep-learning framework for Co n de nsing enhancers and refining boundaries with large-scale functional assays

Bioinformatics (Oxford, England), 2021-08, Vol.37 (Supplement_1), p.i280-i288

2021

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Binding peptide generation for MHC Class I proteins with deep reinforcement learning

Bioinformatics (Oxford, England), 2023-02, Vol.39 (2)

2023

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Source-Free Video Domain Adaptation with Spatial-Temporal-Historical Consistency Learning

2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023, p.14643-14652

2023

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Dual Projection Generative Adversarial Networks for Conditional Image Generation

2021 IEEE/CVF International Conference on Computer Vision (ICCV), 2021, p.14418-14427

2021

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Architecture of the human regulatory network derived from ENCODE data

Rethinking Zero-Shot Learning: A Conditional Visual Classification Perspective

Systematic exploration of essential yeast gene function with temperature-sensitive mutants

TIP: A probabilistic method for identifying transcription factor target genes from ChIP-seq binding profiles

Understanding transcriptional regulation by integrative analysis of transcription factor binding data

Gene expression variability within and between human populations and implications toward disease susceptibility

On TCR binding predictors failing to generalize to unseen peptides

High-order neural networks and kernel methods for peptide-MHC binding prediction

AE-StyleGAN: Improved Training of Style-Based Auto-Encoders

Ranking-Based Convolutional Neural Network Models for Peptide-MHC Class I Binding Prediction

Accelerating deep neural network training with inconsistent stochastic gradient descent

Exploiting the determinants of stochastic gene expression in Saccharomyces cerevisiae for genome-wide prediction of expression noise

Parametric t-Distributed Stochastic Exemplar-Centered Embedding

Model-based autoencoders for imputing discrete single-cell RNA-seq data

Fully convolutional structured LSTM networks for joint 4D medical image segmentation

S3VAE: Self-Supervised Sequential VAE for Representation Disentanglement and Data Generation

Impeller: a path-based heterogeneous graph learning method for spatial transcriptomic data imputation

StyleT2I: Toward Compositional and High-Fidelity Text-to-Image Synthesis

Conditional Image-to-Video Generation with Latent Flow Diffusion Models

DECODE: a Deep-learning framework for Condensing enhancers and refining boundaries with large-scale functional assays

Attentive Variational Information Bottleneck for TCR–peptide interaction prediction

DECODE: a De ep-learning framework for Co n de nsing enhancers and refining boundaries with large-scale functional assays

Binding peptide generation for MHC Class I proteins with deep reinforcement learning

Source-Free Video Domain Adaptation with Spatial-Temporal-Historical Consistency Learning

Dual Projection Generative Adversarial Networks for Conditional Image Generation

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