Martin Renqiang Min

research

∙ 04/25/2023

Exploring Compositional Visual Generation with Latent Classifier Guidance

Diffusion probabilistic models have achieved enormous success in the fie...

0 Changhao Shi, et al. ∙

research

∙ 03/24/2023

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

Conditional image-to-video (cI2V) generation aims to synthesize a new pl...

0 Haomiao Ni, et al. ∙

research

∙ 03/02/2023

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

T cells monitor the health status of cells by identifying foreign peptid...

0 Ziqi Chen, et al. ∙

research

∙ 01/04/2023

Attribute-Centric Compositional Text-to-Image Generation

Despite the recent impressive breakthroughs in text-to-image generation,...

0 Yuren Cong, et al. ∙

research

∙ 03/29/2022

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

Although progress has been made for text-to-image synthesis, previous me...

0 Zhiheng Li, et al. ∙

research

∙ 02/24/2022

Learning Transferable Reward for Query Object Localization with Policy Adaptation

We propose a reinforcement learning based approach to query object local...

2 Tingfeng Li, et al. ∙

research

∙ 10/17/2021

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

StyleGANs have shown impressive results on data generation and manipulat...

15 Ligong Han, et al. ∙

research

∙ 08/20/2021

Dual Projection Generative Adversarial Networks for Conditional Image Generation

Conditional Generative Adversarial Networks (cGANs) extend the standard ...

7 Ligong Han, et al. ∙

research

∙ 03/19/2021

Hopper: Multi-hop Transformer for Spatiotemporal Reasoning

This paper considers the problem of spatiotemporal object-centric reason...

8 Honglu Zhou, et al. ∙

research

∙ 01/19/2021

Disentangled Recurrent Wasserstein Autoencoder

Learning disentangled representations leads to interpretable models and ...

12 Jun Han, et al. ∙

research

∙ 12/08/2020

Molecule Optimization via Fragment-based Generative Models

In drug discovery, molecule optimization is an important step in order t...

0 Ziqi Chen, et al. ∙

research

∙ 12/04/2020

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

T-cell receptors can recognize foreign peptides bound to major histocomp...

0 Ziqi Chen, et al. ∙

research

∙ 06/01/2020

Improving Disentangled Text Representation Learning with Information-Theoretic Guidance

Learning disentangled representations of natural language is essential f...

5 Pengyu Cheng, et al. ∙

research

∙ 05/23/2020

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

We propose a sequential variational autoencoder to learn disentangled re...

31 Yizhe Zhu, et al. ∙

research

∙ 09/13/2019

Rethinking Zero-Shot Learning: A Conditional Visual Classification Perspective

Zero-shot learning (ZSL) aims to recognize instances of unseen classes s...

0 Kai Li, et al. ∙

research

∙ 05/13/2019

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

In spite of its importance, passenger demand prediction is a highly chal...

0 Xiaoyuan Liang, et al. ∙

research

∙ 02/27/2019

Disentangled Deep Autoencoding Regularization for Robust Image Classification

In spite of achieving revolutionary successes in machine learning, deep ...

0 Zhenyu Duan, et al. ∙

research

∙ 11/19/2018

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

Recent studies have demonstrated the vulnerability of deep convolutional...

0 Yao Li, et al. ∙

research

∙ 06/21/2018

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

Conventional embedding methods directly associate each symbol with a con...

0 Ting Chen, et al. ∙

research

∙ 05/24/2018

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

Many deep learning architectures have been proposed to model the composi...

0 Dinghan Shen, et al. ∙

research

∙ 11/08/2017

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

Embedding methods such as word embedding have become pillars for many ap...

0 Ting Chen, et al. ∙

research

∙ 10/23/2017

Convolutional Neural Knowledge Graph Learning

Previous models for learning entity and relationship embeddings of knowl...

0 Feipeng Zhao, et al. ∙

research

∙ 10/01/2017

Video Generation From Text

Generating videos from text has proven to be a significant challenge for...

0 Yitong Li, et al. ∙

research

∙ 09/25/2017

Adaptive Convolutional Filter Generation for Natural Language Understanding

Convolutional neural networks (CNNs) have recently emerged as a popular ...

0 Dinghan Shen, et al. ∙

research

∙ 02/21/2017

Exemplar-Centered Supervised Shallow Parametric Data Embedding

Metric learning methods for dimensionality reduction in combination with...

0 Martin Renqiang Min, et al. ∙

research

∙ 12/22/2016

A Context-aware Attention Network for Interactive Question Answering

Neural network based sequence-to-sequence models in an encoder-decoder f...

0 Huayu Li, et al. ∙

research

∙ 11/23/2016

Adaptive Feature Abstraction for Translating Video to Text

Previous models for video captioning often use the output from a specifi...

0 Yunchen Pu, et al. ∙

research

∙ 08/16/2016

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

Explicit high-order feature interactions efficiently capture essential s...

0 Martin Renqiang Min, et al. ∙

research

∙ 04/29/2015

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

Many real-world applications are associated with structured data, where ...

0 Hongyu Guo, et al. ∙

research

∙ 06/09/2009

Large-Margin kNN Classification Using a Deep Encoder Network

KNN is one of the most popular classification methods, but it often fail...

0 Martin Renqiang Min, et al. ∙

Martin Renqiang Min

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