Martin Renqiang Min

Publication Activity (10 Years)

Years Active: 2007-2024
Publications (10 Years): 68

Top Topics

Boltzmann Machines

Image Generation

Visual Classification

Top Venues

Publications

Yao Wei, Martin Renqiang Min, George Vosselman, Li Erran Li, Michael Ying Yang
Compositional 3D Scene Synthesis with Scene Graph Guided Layout-Shape Generation. CoRR (2024)
Kumaranage Ravindu Yasas Nagasinghe, Honglu Zhou, Malitha Gunawardhana, Martin Renqiang Min, Daniel Harari, Muhammad Haris Khan
Why Not Use Your Textbook? Knowledge-Enhanced Procedure Planning of Instructional Videos. CoRR (2024)
Yuren Cong, Martin Renqiang Min, Li Erran Li, Bodo Rosenhahn, Michael Ying Yang
Attribute-Centric Compositional Text-to-Image Generation. CoRR (2023)
Filippo Grazioli, Pierre Machart, Anja Mösch, Kai Li, Leonardo V. Castorina, Nico Pfeifer, Martin Renqiang Min
Attentive Variational Information Bottleneck for TCR-peptide interaction prediction. Bioinform. 39 (1) (2023)
Changhao Shi, Haomiao Ni, Kai Li, Shaobo Han, Mingfu Liang, Martin Renqiang Min
Exploring Compositional Visual Generation with Latent Classifier Guidance. CVPR Workshops (2023)
Haifeng Xia, Kai Li, Martin Renqiang Min, Zhengming Ding
Few-Shot Video Classification via Representation Fusion and Promotion Learning. ICCV (2023)
Changhao Shi, Haomiao Ni, Kai Li, Shaobo Han, Mingfu Liang, Martin Renqiang Min
Exploring Compositional Visual Generation with Latent Classifier Guidance. CoRR (2023)
Tianxiao Li, Hongyu Guo, Filippo Grazioli, Mark Gerstein, Martin Renqiang Min
Disentangled Wasserstein Autoencoder for T-Cell Receptor Engineering. NeurIPS (2023)
Kai Li, Deep Patel, Erik Kruus, Martin Renqiang Min
Source-Free Video Domain Adaptation with Spatial-Temporal-Historical Consistency Learning. CVPR (2023)
Ziqi Chen, Baoyi Zhang, Hongyu Guo, Prashant S. Emani, Trevor Clancy, Chongming Jiang, Mark Gerstein, Xia Ning, Chao Cheng, Martin Renqiang Min
Binding peptide generation for MHC Class I proteins with deep reinforcement learning. Bioinform. 39 (2) (2023)
Haomiao Ni, Changhao Shi, Kai Li, Sharon X. Huang, Martin Renqiang Min
Conditional Image-to-Video Generation with Latent Flow Diffusion Models. CVPR (2023)
Haomiao Ni, Changhao Shi, Kai Li, Sharon X. Huang, Martin Renqiang Min
Conditional Image-to-Video Generation with Latent Flow Diffusion Models. CoRR (2023)
Ziqi Chen, Martin Renqiang Min, Hongyu Guo, Chao Cheng, Trevor Clancy, Xia Ning
T-Cell Receptor Optimization with Reinforcement Learning and Mutation Polices for Precision Immunotherapy. RECOMB (2023)
Ziqi Chen, Martin Renqiang Min, Hongyu Guo, Chao Cheng, Trevor Clancy, Xia Ning
T-Cell Receptor Optimization with Reinforcement Learning and Mutation Policies for Precesion Immunotherapy. CoRR (2023)
Tingfeng Li, Shaobo Han, Martin Renqiang Min, Dimitris N. Metaxas
Learning Transferable Reward for Query Object Localization with Policy Adaptation. CoRR (2022)
Tingfeng Li, Shaobo Han, Martin Renqiang Min, Dimitris N. Metaxas
Learning Transferable Reward for Query Object Localization with Policy Adaptation. ICLR (2022)
Zhiheng Li, Martin Renqiang Min, Kai Li, Chenliang Xu
StyleT2I: Toward Compositional and High-Fidelity Text-to-Image Synthesis. CVPR (2022)
Ligong Han, Sri Harsha Musunuri, Martin Renqiang Min, Ruijiang Gao, Yu Tian, Dimitris N. Metaxas
AE-StyleGAN: Improved Training of Style-Based Auto-Encoders. WACV (2022)
Yiren Jian, Erik Kruus, Martin Renqiang Min
T-Cell Receptor-Peptide Interaction Prediction with Physical Model Augmented Pseudo-Labeling. KDD (2022)
Zhiheng Li, Martin Renqiang Min, Kai Li, Chenliang Xu
StyleT2I: Toward Compositional and High-Fidelity Text-to-Image Synthesis. CoRR (2022)
Zhan Shi, Hui Liu, Martin Renqiang Min, Christopher Malon, Li Erran Li, Xiaodan Zhu
Retrieval, Analogy, and Composition: A framework for Compositional Generalization in Image Captioning. EMNLP (Findings) (2021)
Yao Li, Martin Renqiang Min, Thomas C. M. Lee, Wenchao Yu, Erik Kruus, Wei Wang, Cho-Jui Hsieh
Towards Robustness of Deep Neural Networks via Regularization. ICCV (2021)
Zhanlin Chen, Jing Zhang, Jason Liu, Yi Dai, Donghoon Lee, Martin Renqiang Min, Min Xu, Mark Gerstein
DECODE: a Deep-learning framework for Condensing enhancers and refining boundaries with large-scale functional assays. Bioinform. 37 (Supplement) (2021)
Ligong Han, Martin Renqiang Min, Anastasis Stathopoulos, Yu Tian, Ruijiang Gao, Asim Kadav, Dimitris N. Metaxas
Dual Projection Generative Adversarial Networks for Conditional Image Generation. ICCV (2021)
Honglu Zhou, Asim Kadav, Farley Lai, Alexandru Niculescu-Mizil, Martin Renqiang Min, Mubbasir Kapadia, Hans Peter Graf
Hopper: Multi-hop Transformer for Spatiotemporal Reasoning. ICLR (2021)
Jun Han, Martin Renqiang Min, Ligong Han, Li Erran Li, Xuan Zhang
Disentangled Recurrent Wasserstein Autoencoder. CoRR (2021)
Honglu Zhou, Asim Kadav, Farley Lai, Alexandru Niculescu-Mizil, Martin Renqiang Min, Mubbasir Kapadia, Hans Peter Graf
Hopper: Multi-hop Transformer for Spatiotemporal Reasoning. CoRR (2021)
Jun Han, Martin Renqiang Min, Ligong Han, Li Erran Li, Xuan Zhang
Disentangled Recurrent Wasserstein Autoencoder. ICLR (2021)
Ligong Han, Sri Harsha Musunuri, Martin Renqiang Min, Ruijiang Gao, Yu Tian, Dimitris N. Metaxas
AE-StyleGAN: Improved Training of Style-Based Auto-Encoders. CoRR (2021)
Ligong Han, Martin Renqiang Min, Anastasis Stathopoulos, Yu Tian, Ruijiang Gao, Asim Kadav, Dimitris N. Metaxas
Dual Projection Generative Adversarial Networks for Conditional Image Generation. CoRR (2021)
Ziqi Chen, Martin Renqiang Min, Srinivasan Parthasarathy, Xia Ning
A deep generative model for molecule optimization via one fragment modification. Nat. Mach. Intell. 3 (12) (2021)
Ziqi Chen, Martin Renqiang Min, Srinivasan Parthasarathy, Xia Ning
Molecule Optimization via Fragment-based Generative Models. CoRR (2020)
Pengyu Cheng, Martin Renqiang Min, Dinghan Shen, Christopher Malon, Yizhe Zhang, Yitong Li, Lawrence Carin
Improving Disentangled Text Representation Learning with Information-Theoretic Guidance. ACL (2020)
Pengyu Cheng, Martin Renqiang Min, Dinghan Shen, Christopher Malon, Yizhe Zhang, Yitong Li, Lawrence Carin
Improving Disentangled Text Representation Learning with Information-Theoretic Guidance. CoRR (2020)
Yizhe Zhu, Martin Renqiang Min, Asim Kadav, Hans Peter Graf
S3VAE: Self-Supervised Sequential VAE for Representation Disentanglement and Data Generation. CoRR (2020)
Yizhe Zhu, Martin Renqiang Min, Asim Kadav, Hans Peter Graf
S3VAE: Self-Supervised Sequential VAE for Representation Disentanglement and Data Generation. CVPR (2020)
Ziqi Chen, Martin Renqiang Min, Xia Ning
Ranking-based Convolutional Neural Network Models for Peptide-MHC Binding Prediction. CoRR (2020)
Kai Li, Martin Renqiang Min, Yun Fu
Rethinking Zero-Shot Learning: A Conditional Visual Classification Perspective. CoRR (2019)
Kai Li, Martin Renqiang Min, Yun Fu
Rethinking Zero-Shot Learning: A Conditional Visual Classification Perspective. ICCV (2019)
Yogesh Balaji, Martin Renqiang Min, Bing Bai, Rama Chellappa, Hans Peter Graf
Conditional GAN with Discriminative Filter Generation for Text-to-Video Synthesis. IJCAI (2019)
Zhenyu Duan, Martin Renqiang Min, Li Erran Li, Mingbo Cai, Yi Xu, Bingbing Ni
Disentangled Deep Autoencoding Regularization for Robust Image Classification. CoRR (2019)
Kai Li, Martin Renqiang Min, Bing Bai, Yun Fu, Hans Peter Graf
On Novel Object Recognition: A Unified Framework for Discriminability and Adaptability. CIKM (2019)
Xiaoyuan Liang, Martin Renqiang Min, Hongyu Guo, Guiling Wang
Learning K-way D-dimensional Discrete Embedding for Hierarchical Data Visualization and Retrieval. IJCAI (2019)
Xiaoyuan Liang, Guiling Wang, Martin Renqiang Min, Yi Qi, Zhu Han
A Deep Spatio-Temporal Fuzzy Neural Network for Passenger Demand Prediction. SDM (2019)
Xiaoyuan Liang, Guiling Wang, Martin Renqiang Min, Yi Qi, Zhu Han
A Deep Spatio-Temporal Fuzzy Neural Network for Passenger Demand Prediction. CoRR (2019)
Yitong Li, Martin Renqiang Min, Dinghan Shen, David E. Carlson, Lawrence Carin
Video Generation From Text. AAAI (2018)
Dinghan Shen, Guoyin Wang, Wenlin Wang, Martin Renqiang Min, Qinliang Su, Yizhe Zhang, Chunyuan Li, Ricardo Henao, Lawrence Carin
Baseline Needs More Love: On Simple Word-Embedding-Based Models and Associated Pooling Mechanisms. ACL (1) (2018)
Bo Zong, Qi Song, Martin Renqiang Min, Wei Cheng, Cristian Lumezanu, Dae-ki Cho, Haifeng Chen
Deep Autoencoding Gaussian Mixture Model for Unsupervised Anomaly Detection. ICLR (Poster) (2018)
Yunchen Pu, Martin Renqiang Min, Zhe Gan, Lawrence Carin
Adaptive Feature Abstraction for Translating Video to Text. AAAI (2018)
Ting Chen, Martin Renqiang Min, Yizhou Sun
Learning K-way D-dimensional Discrete Codes for Compact Embedding Representations. ICML (2018)
Dinghan Shen, Guoyin Wang, Wenlin Wang, Martin Renqiang Min, Qinliang Su, Yizhe Zhang, Chunyuan Li, Ricardo Henao, Lawrence Carin
Baseline Needs More Love: On Simple Word-Embedding-Based Models and Associated Pooling Mechanisms. CoRR (2018)
Martin Renqiang Min, Hongyu Guo, Dinghan Shen
Parametric t-Distributed Stochastic Exemplar-Centered Embedding. ECML/PKDD (1) (2018)
Ting Chen, Martin Renqiang Min, Yizhou Sun
Learning K-way D-dimensional Discrete Codes for Compact Embedding Representations. CoRR (2018)
Dinghan Shen, Martin Renqiang Min, Yitong Li, Lawrence Carin
Learning Context-Aware Convolutional Filters for Text Processing. EMNLP (2018)
Yao Li, Martin Renqiang Min, Wenchao Yu, Cho-Jui Hsieh, Thomas C. M. Lee, Erik Kruus
Optimal Transport Classifier: Defending Against Adversarial Attacks by Regularized Deep Embedding. CoRR (2018)
Yunchen Pu, Martin Renqiang Min, Zhe Gan, Lawrence Carin
Adaptive Feature Abstraction for Translating Video to Language. ICLR (Workshop) (2017)
Martin Renqiang Min, Hongyu Guo, Dongjin Song
Exemplar-centered Supervised Shallow Parametric Data Embedding. IJCAI (2017)
Martin Renqiang Min, Hongyu Guo, Dongjin Song
Exemplar-Centered Supervised Shallow Parametric Data Embedding. CoRR (2017)
Yitong Li, Martin Renqiang Min, Dinghan Shen, David E. Carlson, Lawrence Carin
Video Generation From Text. CoRR (2017)
Huayu Li, Martin Renqiang Min, Yong Ge, Asim Kadav
A Context-aware Attention Network for Interactive Question Answering. KDD (2017)
Ting Chen, Martin Renqiang Min, Yizhou Sun
Learning K-way D-dimensional Discrete Code For Compact Embedding Representations. CoRR (2017)
Martin Renqiang Min, Hongyu Guo, Dinghan Shen
Parametric t-Distributed Stochastic Exemplar-centered Embedding. CoRR (2017)
Dinghan Shen, Martin Renqiang Min, Yitong Li, Lawrence Carin
Adaptive Convolutional Filter Generation for Natural Language Understanding. CoRR (2017)
Huayu Li, Martin Renqiang Min, Yong Ge, Asim Kadav
A Context-aware Attention Network for Interactive Question Answering. CoRR (2016)
Yunchen Pu, Martin Renqiang Min, Zhe Gan, Lawrence Carin
Adaptive Feature Abstraction for Translating Video to Language. CoRR (2016)
Martin Renqiang Min, Hongyu Guo, Dongjin Song
A Shallow High-Order Parametric Approach to Data Visualization and Compression. CoRR (2016)
Linnan Wang, Yi Yang, Martin Renqiang Min, Srimat T. Chakradhar
Accelerating Deep Neural Network Training with Inconsistent Stochastic Gradient Descent. CoRR (2016)
Ke Zhang, Jianwu Xu, Martin Renqiang Min, Guofei Jiang, Konstantinos Pelechrinis, Hui Zhang
Automated IT system failure prediction: A deep learning approach. IEEE BigData (2016)
Pavel P. Kuksa, Martin Renqiang Min, Rishabh Dugar, Mark Gerstein
High-order neural networks and kernel methods for peptide-MHC binding prediction. Bioinform. 31 (22) (2015)
Hongyu Guo, Xiaodan Zhu, Martin Renqiang Min
A Deep Learning Model for Structured Outputs with High-order Interaction. CoRR (2015)
Hao Wu, Martin Renqiang Min, Bing Bai
Deep Semantic Embedding. SMIR@SIGIR (2014)
Martin Renqiang Min, Salim A. Chowdhury, Yanjun Qi, Alex Stewart, Rachel Ostroff
An Integrated Approach To Blood-Based Cancer Diagnosis And Biomarker Discovery. Pacific Symposium on Biocomputing (2014)
Martin Renqiang Min, Xia Ning, Chao Cheng, Mark Gerstein
Interpretable Sparse High-Order Boltzmann Machines. AISTATS (2014)
Sanjay Purushotham, Martin Renqiang Min, C.-C. Jay Kuo, Rachel Ostroff
Factorized sparse learning models with interpretable high order feature interactions. KDD (2014)
Martin Renqiang Min, Laurens van der Maaten, Zineng Yuan, Anthony J. Bonner, Zhaolei Zhang
Deep Supervised t-Distributed Embedding. ICML (2010)
Jingjing Li, Martin Renqiang Min, Anthony J. Bonner, Zhaolei Zhang
A Probabilistic Framework to Improve microRNA Target Prediction by Incorporating Proteomics Data. J. Bioinform. Comput. Biol. 7 (6) (2009)
Martin Renqiang Min, Rui Kuang, Anthony J. Bonner, Zhaolei Zhang
Learning Random-Walk Kernels for Protein Remote Homology Identification and Motif Discovery. SDM (2009)
Martin Renqiang Min, David A. Stanley, Zineng Yuan, Anthony J. Bonner, Zhaolei Zhang
A Deep Non-linear Feature Mapping for Large-Margin kNN Classification. ICDM (2009)
Martin Renqiang Min, David A. Stanley, Zineng Yuan, Anthony J. Bonner, Zhaolei Zhang
Large-Margin kNN Classification Using a Deep Encoder Network CoRR (2009)
Martin Renqiang Min, Anthony J. Bonner, Zhaolei Zhang
Modifying kernels using label information improves SVM classification performance. ICMLA (2007)