Martin Renqiang Min

According to our database, Martin Renqiang Min authored at least 68 papers between 2007 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Compositional 3D Scene Synthesis with Scene Graph Guided Layout-Shape Generation.

Yao Wei, Martin Renqiang Min, George Vosselman, Li Erran Li, Michael Ying Yang

CoRR, 2024

Why Not Use Your Textbook? Knowledge-Enhanced Procedure Planning of Instructional Videos.

Kumaranage Ravindu Yasas Nagasinghe, Honglu Zhou, Malitha Gunawardhana, Martin Renqiang Min, Daniel Harari, Muhammad Haris Khan

CoRR, 2024

2023

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

Ziqi Chen, Baoyi Zhang, Hongyu Guo, Prashant S. Emani, Trevor Clancy, Chongming Jiang, Mark Gerstein, Xia Ning, Chao Cheng, Martin Renqiang Min

Bioinform., February, 2023

Attentive Variational Information Bottleneck for TCR-peptide interaction prediction.

Filippo Grazioli, Pierre Machart, Anja Mösch, Kai Li, Leonardo V. Castorina, Nico Pfeifer, Martin Renqiang Min

Bioinform., January, 2023

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

Ziqi Chen, Martin Renqiang Min, Hongyu Guo, Chao Cheng, Trevor Clancy, Xia Ning

CoRR, 2023

Attribute-Centric Compositional Text-to-Image Generation.

Yuren Cong, Martin Renqiang Min, Li Erran Li, Bodo Rosenhahn, Michael Ying Yang

CoRR, 2023

T-Cell Receptor Optimization with Reinforcement Learning and Mutation Polices for Precision Immunotherapy.

Ziqi Chen, Martin Renqiang Min, Hongyu Guo, Chao Cheng, Trevor Clancy, Xia Ning

Proceedings of the Research in Computational Molecular Biology, 2023

Disentangled Wasserstein Autoencoder for T-Cell Receptor Engineering.

Tianxiao Li, Hongyu Guo, Filippo Grazioli, Mark Gerstein, Martin Renqiang Min

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Few-Shot Video Classification via Representation Fusion and Promotion Learning.

Haifeng Xia, Kai Li, Martin Renqiang Min, Zhengming Ding

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Exploring Compositional Visual Generation with Latent Classifier Guidance.

Changhao Shi, Haomiao Ni, Kai Li, Shaobo Han, Mingfu Liang, Martin Renqiang Min

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

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

Haomiao Ni, Changhao Shi, Kai Li, Sharon X. Huang, Martin Renqiang Min

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

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

Kai Li, Deep Patel, Erik Kruus, Martin Renqiang Min

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

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

Ligong Han, Sri Harsha Musunuri, Martin Renqiang Min, Ruijiang Gao, Yu Tian, Dimitris N. Metaxas

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2022

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

Yiren Jian, Erik Kruus, Martin Renqiang Min

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Learning Transferable Reward for Query Object Localization with Policy Adaptation.

Tingfeng Li, Shaobo Han, Martin Renqiang Min, Dimitris N. Metaxas

Proceedings of the Tenth International Conference on Learning Representations, 2022

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

Zhiheng Li, Martin Renqiang Min, Kai Li, Chenliang Xu

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021

A deep generative model for molecule optimization via one fragment modification.

Ziqi Chen, Martin Renqiang Min, Srinivasan Parthasarathy, Xia Ning

Nat. Mach. Intell., 2021

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

Zhanlin Chen, Jing Zhang, Jason Liu, Yi Dai, Donghoon Lee, Martin Renqiang Min, Min Xu, Mark Gerstein

Bioinform., 2021

Hopper: Multi-hop Transformer for Spatiotemporal Reasoning.

Honglu Zhou, Asim Kadav, Farley Lai, Alexandru Niculescu-Mizil, Martin Renqiang Min, Mubbasir Kapadia, Hans Peter Graf

Proceedings of the 9th International Conference on Learning Representations, 2021

Disentangled Recurrent Wasserstein Autoencoder.

Jun Han, Martin Renqiang Min, Ligong Han, Li Erran Li, Xuan Zhang

Proceedings of the 9th International Conference on Learning Representations, 2021

Towards Robustness of Deep Neural Networks via Regularization.

Yao Li, Martin Renqiang Min, Thomas C. M. Lee, Wenchao Yu, Erik Kruus, Wei Wang, Cho-Jui Hsieh

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Dual Projection Generative Adversarial Networks for Conditional Image Generation.

Ligong Han, Martin Renqiang Min, Anastasis Stathopoulos, Yu Tian, Ruijiang Gao, Asim Kadav, Dimitris N. Metaxas

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

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

Zhan Shi, Hui Liu, Martin Renqiang Min, Christopher Malon, Li Erran Li, Xiaodan Zhu

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2021, 2021

2020

Molecule Optimization via Fragment-based Generative Models.

Ziqi Chen, Martin Renqiang Min, Srinivasan Parthasarathy, Xia Ning

CoRR, 2020

Ranking-based Convolutional Neural Network Models for Peptide-MHC Binding Prediction.

Ziqi Chen, Martin Renqiang Min, Xia Ning

CoRR, 2020

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

Yizhe Zhu, Martin Renqiang Min, Asim Kadav, Hans Peter Graf

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Improving Disentangled Text Representation Learning with Information-Theoretic Guidance.

Pengyu Cheng, Martin Renqiang Min, Dinghan Shen, Christopher Malon, Yizhe Zhang, Yitong Li, Lawrence Carin

Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

2019

CNN-based Dual-Chain Models for Knowledge Graph Learning.

Bo Peng, Renqiang Min, Xia Ning

CoRR, 2019

Disentangled Deep Autoencoding Regularization for Robust Image Classification.

Zhenyu Duan, Martin Renqiang Min, Li Erran Li, Mingbo Cai, Yi Xu, Bingbing Ni

CoRR, 2019

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

Xiaoyuan Liang, Guiling Wang, Martin Renqiang Min, Yi Qi, Zhu Han

Proceedings of the 2019 SIAM International Conference on Data Mining, 2019

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

Xiaoyuan Liang, Martin Renqiang Min, Hongyu Guo, Guiling Wang

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

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

Yogesh Balaji, Martin Renqiang Min, Bing Bai, Rama Chellappa, Hans Peter Graf

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Rethinking Zero-Shot Learning: A Conditional Visual Classification Perspective.

Kai Li, Martin Renqiang Min, Yun Fu

Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

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

Kai Li, Martin Renqiang Min, Bing Bai, Yun Fu, Hans Peter Graf

Proceedings of the 28th ACM International Conference on Information and Knowledge Management, 2019

2018

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

Yao Li, Martin Renqiang Min, Wenchao Yu, Cho-Jui Hsieh, Thomas C. M. Lee, Erik Kruus

CoRR, 2018

Parametric t-Distributed Stochastic Exemplar-Centered Embedding.

Martin Renqiang Min, Hongyu Guo, Dinghan Shen

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2018

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

Yang Gao, Jeff M. Phillips, Yan Zheng, Renqiang Min, P. Thomas Fletcher, Guido Gerig

Proceedings of the 15th IEEE International Symposium on Biomedical Imaging, 2018

Learning K-way D-dimensional Discrete Codes for Compact Embedding Representations.

Ting Chen, Martin Renqiang Min, Yizhou Sun

Proceedings of the 35th International Conference on Machine Learning, 2018

Deep Autoencoding Gaussian Mixture Model for Unsupervised Anomaly Detection.

Bo Zong, Qi Song, Martin Renqiang Min, Wei Cheng, Cristian Lumezanu, Dae-ki Cho, Haifeng Chen

Proceedings of the 6th International Conference on Learning Representations, 2018

Learning Context-Aware Convolutional Filters for Text Processing.

Dinghan Shen, Martin Renqiang Min, Yitong Li, Lawrence Carin

Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31, 2018

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

Dinghan Shen, Guoyin Wang, Wenlin Wang, Martin Renqiang Min, Qinliang Su, Yizhe Zhang, Chunyuan Li, Ricardo Henao, Lawrence Carin

Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, 2018

Adaptive Feature Abstraction for Translating Video to Text.

Yunchen Pu, Martin Renqiang Min, Zhe Gan, Lawrence Carin

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

Video Generation From Text.

Yitong Li, Martin Renqiang Min, Dinghan Shen, David E. Carlson, Lawrence Carin

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017

Accelerating deep neural network training with inconsistent stochastic gradient descent.

Linnan Wang, Yi Yang, Renqiang Min, Srimat T. Chakradhar

Neural Networks, 2017

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

Ting Chen, Martin Renqiang Min, Yizhou Sun

CoRR, 2017

Adaptive Convolutional Filter Generation for Natural Language Understanding.

Dinghan Shen, Martin Renqiang Min, Yitong Li, Lawrence Carin

CoRR, 2017

A Context-aware Attention Network for Interactive Question Answering.

Huayu Li, Martin Renqiang Min, Yong Ge, Asim Kadav

Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, NS, Canada, August 13, 2017

Exemplar-centered Supervised Shallow Parametric Data Embedding.

Martin Renqiang Min, Hongyu Guo, Dongjin Song

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Adaptive Feature Abstraction for Translating Video to Language.

Yunchen Pu, Martin Renqiang Min, Zhe Gan, Lawrence Carin

Proceedings of the 5th International Conference on Learning Representations, 2017

2016

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

Martin Renqiang Min, Hongyu Guo, Dongjin Song

CoRR, 2016

Automated IT system failure prediction: A deep learning approach.

Ke Zhang, Jianwu Xu, Martin Renqiang Min, Guofei Jiang, Konstantinos Pelechrinis, Hui Zhang

Proceedings of the 2016 IEEE International Conference on Big Data (IEEE BigData 2016), 2016

2015

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

Hongyu Guo, Xiaodan Zhu, Martin Renqiang Min

CoRR, 2015

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

Pavel P. Kuksa, Martin Renqiang Min, Rishabh Dugar, Mark Gerstein

Bioinform., 2015

2014

Deep Semantic Embedding.

Hao Wu, Martin Renqiang Min, Bing Bai

Proceedings of Workshop on Semantic Matching in Information Retrieval co-located with the 37th international ACM SIGIR conference on research and development in information retrieval, 2014

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

Martin Renqiang Min, Salim A. Chowdhury, Yanjun Qi, Alex Stewart, Rachel Ostroff

Proceedings of the Biocomputing 2014: Proceedings of the Pacific Symposium, 2014

Factorized sparse learning models with interpretable high order feature interactions.

Sanjay Purushotham, Martin Renqiang Min, C.-C. Jay Kuo, Rachel Ostroff

Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2014

Interpretable Sparse High-Order Boltzmann Machines.

Martin Renqiang Min, Xia Ning, Chao Cheng, Mark Gerstein

Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, 2014

2012

PhenoM: a database of morphological phenotypes caused by mutation of essential genes in <i>Saccharomyces cerevisiae</i>.

Ke Jin, Jingjing Li, Frederick S. Vizeacoumar, Zhijian Li, Renqiang Min, Lee Zamparo, Franco J. Vizeacoumar, Alessandro Datti, Brenda J. Andrews, Charles Boone, Zhaolei Zhang

Nucleic Acids Res., 2012

2011

Machine Learning Approaches to Biological Sequence and Phenotype Data Analysis.

Renqiang Min

PhD thesis, 2011

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

Chao Cheng, Renqiang Min, Mark Gerstein

Bioinform., 2011

2010

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

Jingjing Li, Yu Liu, TaeHyung Kim, Renqiang Min, Zhaolei Zhang

PLoS Comput. Biol., 2010

Deep Supervised t-Distributed Embedding.

Martin Renqiang Min, Laurens van der Maaten, Zineng Yuan, Anthony J. Bonner, Zhaolei Zhang

Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010

2009

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

Renqiang Min, Anthony J. Bonner, Jingjing Li, Zhaolei Zhang

J. Comput. Biol., 2009

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

Jingjing Li, Martin Renqiang Min, Anthony J. Bonner, Zhaolei Zhang

J. Bioinform. Comput. Biol., 2009

Large-Margin kNN Classification Using a Deep Encoder Network

Martin Renqiang Min, David A. Stanley, Zineng Yuan, Anthony J. Bonner, Zhaolei Zhang

CoRR, 2009

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

Martin Renqiang Min, Rui Kuang, Anthony J. Bonner, Zhaolei Zhang

Proceedings of the SIAM International Conference on Data Mining, 2009

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

Martin Renqiang Min, David A. Stanley, Zineng Yuan, Anthony J. Bonner, Zhaolei Zhang

Proceedings of the ICDM 2009, 2009

2007

Modifying kernels using label information improves SVM classification performance.

Martin Renqiang Min, Anthony J. Bonner, Zhaolei Zhang

Proceedings of the Sixth International Conference on Machine Learning and Applications, 2007