Martin Renqiang Min

发表

Gene Expression Variability within and between Human Populations and Implications toward Disease Susceptibility

Yu Liu, Zhaolei Zhang, Jingjing Li, 2010, PLoS Comput. Biol..

Deep Semantic Embedding

Hao Wu, Bing Bai, Martin Renqiang Min, 2014, SMIR@SIGIR.

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

Mark Gerstein, Martin Renqiang Min, Chao Cheng, 2011, Bioinform..

Parametric t-Distributed Stochastic Exemplar-centered Embedding pdf

Hongyu Guo, Martin Renqiang Min, Dinghan Shen, 2017, ECML/PKDD.

Learning K-way D-dimensional Discrete Embedding for Hierarchical Data Visualization and Retrieval

Hongyu Guo, Martin Renqiang Min, Guiling Wang, 2019, IJCAI.

Disentangled Recurrent Wasserstein Autoencoder pdf

Martin Renqiang Min, Erran L. Li, Jun Han, 2021, ICLR.

Adaptive Feature Abstraction for Translating Video to Text

Zhe Gan, Lawrence Carin, Martin Renqiang Min, 2018, AAAI.

Learning Context-Aware Convolutional Filters for Text Processing

Yitong Li, Lawrence Carin, Martin Renqiang Min, 2018, EMNLP.

Baseline Needs More Love: On Simple Word-Embedding-Based Models and Associated Pooling Mechanisms

Guoyin Wang, Lawrence Carin, Martin Renqiang Min, 2018, ACL.

Convolutional Neural Knowledge Graph Learning pdf

Chen Shen, Martin Renqiang Min, Amit Chakraborty, 2017, ArXiv.

A Deep Non-linear Feature Mapping for Large-Margin kNN Classification

Zhaolei Zhang, Martin Renqiang Min, Anthony J. Bonner, 2009, 2009 Ninth IEEE International Conference on Data Mining.

Large-Margin kNN Classification Using a Deep Encoder Network pdf

Zhaolei Zhang, Martin Renqiang Min, Anthony J. Bonner, 2009, ArXiv.

2016 Ieee International Conference on Big Data (big Data) Automated It System Failure Prediction: a Deep Learning Approach

Ke Zhang, Martin Renqiang Min, Konstantinos Pelechrinis, 2022 .

Rethinking Zero-Shot Learning: A Conditional Visual Classification Perspective

Yun Fu, Kai Li, Martin Renqiang Min, 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).

A Shallow High-Order Parametric Approach to Data Visualization and Compression pdf

Hongyu Guo, Martin Renqiang Min, Dongjin Song, 2016, ArXiv.

Disentangled Deep Autoencoding Regularization for Robust Image Classification pdf

Bingbing Ni, Martin Renqiang Min, Yi Xu, 2019, ArXiv.

Learning K-way D-dimensional Discrete Code For Compact Embedding Representations

Yizhou Sun, Martin Renqiang Min, Ting Chen, 2017, ICML.

Deep Autoencoding Gaussian Mixture Model for Unsupervised Anomaly Detection

Bo Zong, Wei Cheng, Haifeng Chen, 2018, ICLR.

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

Asim Kadav, Martin Renqiang Min, Yizhe Zhu, 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Modifying kernels using label information improves SVM classification performance

Zhaolei Zhang, Martin Renqiang Min, Anthony J. Bonner, 2007, Sixth International Conference on Machine Learning and Applications (ICMLA 2007).

Deep Supervised t-Distributed Embedding

Zhaolei Zhang, Martin Renqiang Min, Laurens van der Maaten, 2010, ICML.

TFGAN: Improving Conditioning for Text-to-Video Synthesis

Rama Chellappa, Martin Renqiang Min, Bing Bai, 2018 .

Conditional GAN with Discriminative Filter Generation for Text-to-Video Synthesis

Rama Chellappa, Martin Renqiang Min, Bing Bai, 2019, IJCAI.

PhenoM: a database of morphological phenotypes caused by mutation of essential genes in Saccharomyces cerevisiae

Zhaolei Zhang, Jingjing Li, Martin Renqiang Min, 2011, Nucleic Acids Res..

Learned Random-Walk Kernels and Empirical-Map Kernels for Protein Sequence Classification

Zhaolei Zhang, Jingjing Li, Martin Renqiang Min, 2009, J. Comput. Biol..

Model-Based Autoencoders for Imputing Discrete single-cell RNA-seq Data.

Martin Renqiang Min, Zhi Wei, Tian Tian, 2020, Methods.

Molecule Optimization via Fragment-based Generative Models pdf

Srinivasan Parthasarathy, Martin Renqiang Min, Ziqi Chen, 2020, ArXiv.

Video Generation From Text

Yitong Li, Lawrence Carin, Martin Renqiang Min, 2017, AAAI.

Defending Against Adversarial Examples by Regularized Deep Embedding

Martin Renqiang Min, Thomas C. M. Lee, Cho-Jui Hsieh, 2019 .

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

Guido Gerig, Yang Gao, Yan Zheng, 2018, 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018).

Adaptive Feature Abstraction for Translating Video to Language pdf

Zhe Gan, Lawrence Carin, Martin Renqiang Min, 2017, ICLR.

Learning Random-Walk Kernels for Protein Remote Homology Identification and Motif Discovery

Zhaolei Zhang, Martin Renqiang Min, Anthony J. Bonner, 2009, SDM.

An Integrated Approach To Blood-Based Cancer Diagnosis And Biomarker Discovery

Yanjun Qi, Rachel Ostroff, Martin Renqiang Min, 2013, Pacific Symposium on Biocomputing.

On Novel Object Recognition: A Unified Framework for Discriminability and Adaptability

Yun Fu, Martin Renqiang Min, Bing Bai, 2019, CIKM.

Learning Context-Sensitive Convolutional Filters for Text Processing

Lawrence Carin, Martin Renqiang Min, Dinghan Shen, 2017 .

A Deep Spatio-Temporal Fuzzy Neural Network for Passenger Demand Prediction pdf

Zhu Han, Martin Renqiang Min, Guiling Wang, 2019, SDM.

Adaptive Convolutional Filter Generation for Natural Language Understanding pdf

Lawrence Carin, Martin Renqiang Min, Dinghan Shen, 2017, ArXiv.

Interpretable Sparse High-Order Boltzmann Machines

Mark Gerstein, Martin Renqiang Min, Xia Ning, 2014, AISTATS.

A Deep Learning Model for Structured Outputs with High-order Interaction pdf

Hongyu Guo, Martin Renqiang Min, Xiao-Dan Zhu, 2015, ArXiv.

On the Use of Word Embeddings Alone to Represent Natural Language Sequences

Lawrence Carin, Martin Renqiang Min, Dinghan Shen, 2018 .

A Context-aware Attention Network for Interactive Question Answering

Asim Kadav, Martin Renqiang Min, Huayu Li, 2016, KDD.

A Probabilistic Framework to Improve microRNA Target Prediction by Incorporating Proteomics Data

Zhaolei Zhang, Jingjing Li, Martin Renqiang Min, 2009, J. Bioinform. Comput. Biol..

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

Mark Gerstein, Martin Renqiang Min, Pavel P. Kuksa, 2015, Bioinform..

Exemplar-centered Supervised Shallow Parametric Data Embedding

Hongyu Guo, Martin Renqiang Min, Dongjin Song, 2017, IJCAI.

Network Reparameterization for Unseen Class Categorization

Yun Fu, Kai Li, Martin Renqiang Min, 2018 .

Optimal Transport Classifier: Defending Against Adversarial Attacks by Regularized Deep Embedding pdf

Cho-Jui Hsieh, Martin Renqiang Min, Yao Li, 2018, ArXiv.

Improving Disentangled Text Representation Learning with Information-Theoretic Guidance pdf

Lawrence Carin, Martin Renqiang Min, Dinghan Shen, 2020, ACL.

Factorized sparse learning models with interpretable high order feature interactions

Rachel Ostroff, C.-C. Jay Kuo, Martin Renqiang Min, 2014, KDD.

Accelerating Deep Neural Network Training with Inconsistent Stochastic Gradient Descent

Yi Yang, Martin Renqiang Min, Srimat T. Chakradhar, 2016, Neural Networks.

Hopper: Multi-hop Transformer for Spatiotemporal Reasoning pdf

Martin Renqiang Min, Hans Peter Graf, Honglu Zhou, 2021, ICLR 2021 Poster.

Disentangled Recurrent Wasserstein Autoencoder pdf

Martin Renqiang Min, Li Erran Li, Xuan Zhang, 2021, ICLR 2021 Spotlight.

Hopper: Multi-hop Transformer for Spatiotemporal Reasoning pdf

Asim Kadav, Martin Renqiang Min, Farley Lai, 2021, ICLR.

Dual Projection Generative Adversarial Networks for Conditional Image Generation pdf

Asim Kadav, Dimitris N. Metaxas, Martin Renqiang Min, 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV).

A deep generative model for molecule optimization via one fragment modification

Srinivasan Parthasarathy, Martin Renqiang Min, Xia Ning, 2020, Nature Machine Intelligence.

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

Dimitris N. Metaxas, Martin Renqiang Min, Dimitris Metaxas, 2021, 2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV).

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

Jason Liu, Donghoon Lee, Mark Gerstein, 2021, bioRxiv.

Retrieval, Analogy, and Composition: A framework for Compositional Generalization in Image Captioning

Martin Renqiang Min, Christopher Malon, Zhan Shi, 2021, EMNLP.

∼ N ( 0 , 1 ) Video Generator Video Discriminator Real ? Fake ?

Martin Renqiang Min, L. Carin, Yitong Li, 2017 .

A Context-aware Attention Network for Interactive Question Answering

Martin Renqiang Min, Martin Renqiang Min, Asim Kadav, 2016, KDD.

Recent work often develops a probabilistic model of the caption , conditioned on a video

Martin Renqiang Min, Yunchen Pu, 2017 .

Fast Nonnegative Matrix Factorization with Rank-one ADMM

Martin Renqiang Min, Dongjin Song, Martin Renqiang Min, 2014 .

Weight-based Neural Network Interpretability using Activation Tuning and Personalized Products

Martin Renqiang Min, M. Gerstein, S. Negahban, 2020 .

On TCR binding predictors failing to generalize to unseen peptides

Martin Renqiang Min, Martin Renqiang Min, Pierre Machart, 2022, Frontiers in Immunology.

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

Martin Renqiang Min, K. Li, Martin Renqiang Min, 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Attribute-Centric Compositional Text-to-Image Generation

Martin Renqiang Min, Erran L. Li, B. Rosenhahn, 2023, ArXiv.

T-Cell Receptor Optimization with Reinforcement Learning and Mutation Policies for Precesion Immunotherapy

Martin Renqiang Min, Xia Ning, T. Clancy, 2023, RECOMB.

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

Martin Renqiang Min, Xia Ning, Martin Renqiang Min, 2020, Frontiers in Molecular Biosciences.

Learning Disentangled Representations for T Cell Receptor Design

Martin Renqiang Min, M. Gerstein, Hongyu Guo, 2022, 2210.08171.

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

Martin Renqiang Min, Sharon X. Huang, Martin Renqiang Min, 2023, 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Towards Robustness of Deep Neural Networks via Regularization

Martin Renqiang Min, Cho-Jui Hsieh, E. Kruus, 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV).

T-Cell Receptor-Peptide Interaction Prediction with Physical Model Augmented Pseudo-Labeling

Martin Renqiang Min, E. Kruus, Yiren Jian, 2022, KDD.

Exploring Compositional Visual Generation with Latent Classifier Guidance

Martin Renqiang Min, Shaobo Han, Kaican Li, 2023, 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).

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

Martin Renqiang Min, Prashant S. Emani, M. Gerstein, 2023, Bioinform..

Attentive Variational Information Bottleneck for TCR–peptide interaction prediction

Martin Renqiang Min, Martin Renqiang Min, Pierre Machart, 2022, Bioinform..

Learning Transferable Reward for Query Object Localization with Policy Adaptation

Dimitris N. Metaxas, Martin Renqiang Min, Shaobo Han, 2022, International Conference on Learning Representations.

Turtling: a time-aware neural topic model on NIH grant data

Martin Renqiang Min, Jing Zhang, Ruiyi Zhang, 2023, Bioinformatics advances.