Search Results for author: Ruizhi Deng

Found 9 papers, 4 papers with code

Continuous-time Particle Filtering for Latent Stochastic Differential Equations

no code implementations1 Sep 2022 Ruizhi Deng, Greg Mori, Andreas M. Lehrmann

Particle filtering is a standard Monte-Carlo approach for a wide range of sequential inference tasks.

Continuous Latent Process Flows

1 code implementation NeurIPS 2021 Ruizhi Deng, Marcus A. Brubaker, Greg Mori, Andreas M. Lehrmann

Partial observations of continuous time-series dynamics at arbitrary time stamps exist in many disciplines.

Time Series Time Series Analysis

Adaptive Appearance Rendering

1 code implementation24 Apr 2021 Mengyao Zhai, Ruizhi Deng, Jiacheng Chen, Lei Chen, Zhiwei Deng, Greg Mori

Hence, we develop an approach based on intermediate representations of poses and appearance: our pose-guided appearance rendering network firstly encodes the targets' poses using an encoder-decoder neural network.

Video Generation

Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows

1 code implementation NeurIPS 2020 Ruizhi Deng, Bo Chang, Marcus A. Brubaker, Greg Mori, Andreas Lehrmann

Normalizing flows transform a simple base distribution into a complex target distribution and have proved to be powerful models for data generation and density estimation.

Density Estimation Irregular Time Series +2

Variational Hyper RNN for Sequence Modeling

no code implementations24 Feb 2020 Ruizhi Deng, Yanshuai Cao, Bo Chang, Leonid Sigal, Greg Mori, Marcus A. Brubaker

In this work, we propose a novel probabilistic sequence model that excels at capturing high variability in time series data, both across sequences and within an individual sequence.

Time Series Time Series Analysis

Point Process Flows

no code implementations18 Oct 2019 Nazanin Mehrasa, Ruizhi Deng, Mohamed Osama Ahmed, Bo Chang, JiaWei He, Thibaut Durand, Marcus Brubaker, Greg Mori

Event sequences can be modeled by temporal point processes (TPPs) to capture their asynchronous and probabilistic nature.

Point Processes

Sparsely Aggregated Convolutional Networks

2 code implementations ECCV 2018 Ligeng Zhu, Ruizhi Deng, Michael Maire, Zhiwei Deng, Greg Mori, Ping Tan

We explore a key architectural aspect of deep convolutional neural networks: the pattern of internal skip connections used to aggregate outputs of earlier layers for consumption by deeper layers.

Learning to Forecast Videos of Human Activity with Multi-granularity Models and Adaptive Rendering

no code implementations5 Dec 2017 Mengyao Zhai, Jiacheng Chen, Ruizhi Deng, Lei Chen, Ligeng Zhu, Greg Mori

An architecture combining a hierarchical temporal model for predicting human poses and encoder-decoder convolutional neural networks for rendering target appearances is proposed.

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