167 citations · 457 across the 38 of their papers we have counts for
11 papers · 1 filter
Learning Energy-Based Models by Cooperative Diffusion Recovery Likelihood
Yaxuan Zhu, Jianwen Xie, Yingnian Wu +1
Training energy-based models (EBMs) on high-dimensional data can be both challenging and time-consuming, and there exists a noticeable gap in sample quality between EBMs and other…
A Tale of Two Latent Flows: Learning Latent Space Normalizing Flow with Short-run Langevin Flow for Approximate Inference
Jianwen Xie, Yaxuan Zhu, Yifei Xu +2
We study a normalizing flow in the latent space of a top-down generator model, in which the normalizing flow model plays the role of the informative prior model of the generator. W…
A Tale of Two Flows: Cooperative Learning of Langevin Flow and Normalizing Flow Toward Energy-Based Model
Jianwen Xie, Yaxuan Zhu, Jun Li +1
This paper studies the cooperative learning of two generative flow models, in which the two models are iteratively updated based on the jointly synthesized examples. The first flow…
Learning Energy-Based Model with Variational Auto-Encoder as Amortized Sampler
Jianwen Xie, Zilong Zheng, Ping Li
Due to the intractable partition function, training energy-based models (EBMs) by maximum likelihood requires Markov chain Monte Carlo (MCMC) sampling to approximate the gradient o…
Representation Learning: A Statistical Perspective
Jianwen Xie, Ruiqi Gao, Erik Nijkamp +2
Learning representations of data is an important problem in statistics and machine learning. While the origin of learning representations can be traced back to factor analysis and…
Cooperative Training of Fast Thinking Initializer and Slow Thinking Solver for Conditional Learning
Jianwen Xie, Zilong Zheng, Xiaolin Fang +2
This paper studies the problem of learning the conditional distribution of a high-dimensional output given an input, where the output and input may belong to two different domains,…
Learning Dynamic Generator Model by Alternating Back-Propagation Through Time
Jianwen Xie, Ruiqi Gao, Zilong Zheng +2
This paper studies the dynamic generator model for spatial-temporal processes such as dynamic textures and action sequences in video data. In this model, each time frame of the vid…
Learning Grid Cells as Vector Representation of Self-Position Coupled with Matrix Representation of Self-Motion
Ruiqi Gao, Jianwen Xie, Song-Chun Zhu +1
This paper proposes a representational model for grid cells. In this model, the 2D self-position of the agent is represented by a high-dimensional vector, and the 2D self-motion or…
Cooperative Training of Descriptor and Generator Networks
Jianwen Xie, Yang Lu, Ruiqi Gao +2
This paper studies the cooperative training of two generative models for image modeling and synthesis. Both models are parametrized by convolutional neural networks (ConvNets). The…
Synthesizing Dynamic Patterns by Spatial-Temporal Generative ConvNet
Jianwen Xie, Song-Chun Zhu, Ying Nian Wu
Video sequences contain rich dynamic patterns, such as dynamic texture patterns that exhibit stationarity in the temporal domain, and action patterns that are non-stationary in eit…
A Theory of Generative ConvNet
Jianwen Xie, Yang Lu, Song-Chun Zhu +1
We show that a generative random field model, which we call generative ConvNet, can be derived from the commonly used discriminative ConvNet, by assuming a ConvNet for multi-catego…