Zhang, Ruixiang

20 publications

AISTATS 2025 Composition and Control with Distilled Energy Diffusion Models and Sequential Monte Carlo James Thornton, Louis Béthune, Ruixiang Zhang, Arwen Bradley, Preetum Nakkiran, Shuangfei Zhai

NeurIPS 2025 Discrete Neural Flow Samplers with Locally Equivariant Transformer Zijing Ou, Ruixiang Zhang, Yingzhen Li

NeurIPS 2025 Flexible Language Modeling in Continuous Space with Transformer-Based Autoregressive Flows Ruixiang Zhang, Shuangfei Zhai, Jiatao Gu, Yizhe Zhang, Huangjie Zheng, Tianrong Chen, Miguel Ángel Bautista, Joshua M. Susskind, Navdeep Jaitly

TMLR 2025 Improving GFlowNets for Text-to-Image Diffusion Alignment Dinghuai Zhang, Yizhe Zhang, Jiatao Gu, Ruixiang Zhang, Joshua M. Susskind, Navdeep Jaitly, Shuangfei Zhai

ICML 2025 Normalizing Flows Are Capable Generative Models Shuangfei Zhai, Ruixiang Zhang, Preetum Nakkiran, David Berthelot, Jiatao Gu, Huangjie Zheng, Tianrong Chen, Miguel Ángel Bautista, Navdeep Jaitly, Joshua M. Susskind

NeurIPS 2025 STARFlow: Scaling Latent Normalizing Flows for High-Resolution Image Synthesis Jiatao Gu, Tianrong Chen, David Berthelot, Huangjie Zheng, Yuyang Wang, Ruixiang Zhang, Laurent Dinh, Miguel Ángel Bautista, Joshua M. Susskind, Shuangfei Zhai

ICML 2025 Target Concrete Score Matching: A Holistic Framework for Discrete Diffusion Ruixiang Zhang, Shuangfei Zhai, Yizhe Zhang, James Thornton, Zijing Ou, Joshua M. Susskind, Navdeep Jaitly

ICLRW 2024 How Far Are We from Intelligent Visual Deductive Reasoning? Yizhe Zhang, He Bai, Ruixiang Zhang, Jiatao Gu, Shuangfei Zhai, Joshua M. Susskind, Navdeep Jaitly

ICMLW 2024 Improving GFlowNets for Text-to-Image Diffusion Alignment Dinghuai Zhang, Yizhe Zhang, Jiatao Gu, Ruixiang Zhang, Joshua M. Susskind, Navdeep Jaitly, Shuangfei Zhai

ICMLW 2024 Improving GFlowNets for Text-to-Image Diffusion Alignment Dinghuai Zhang, Yizhe Zhang, Jiatao Gu, Ruixiang Zhang, Joshua M. Susskind, Navdeep Jaitly, Shuangfei Zhai

ICLR 2023 Analog Bits: Generating Discrete Data Using Diffusion Models with Self-Conditioning Ting Chen, Ruixiang Zhang, Geoffrey Hinton

ICLR 2023 Robust and Controllable Object-Centric Learning Through Energy-Based Models Ruixiang Zhang, Tong Che, Boris Ivanovic, Renhao Wang, Marco Pavone, Yoshua Bengio, Liam Paull

ICLR 2022 Learning Representation from Neural Fisher Kernel with Low-Rank Approximation Ruixiang Zhang, Shuangfei Zhai, Etai Littwin, Joshua M. Susskind

AAAI 2021 Deep Verifier Networks: Verification of Deep Discriminative Models with Deep Generative Models Tong Che, Xiaofeng Liu, Site Li, Yubin Ge, Ruixiang Zhang, Caiming Xiong, Yoshua Bengio

ICCV 2021 RPVNet: A Deep and Efficient Range-Point-Voxel Fusion Network for LiDAR Point Cloud Segmentation Jianyun Xu, Ruixiang Zhang, Jian Dou, Yushi Zhu, Jie Sun, Shiliang Pu

ICML 2020 Learning Structured Latent Factors from Dependent Data:A Generative Model Framework from Information-Theoretic Perspective Ruixiang Zhang, Masanori Koyama, Katsuhiko Ishiguro

ICML 2020 Perceptual Generative Autoencoders Zijun Zhang, Ruixiang Zhang, Zongpeng Li, Yoshua Bengio, Liam Paull

NeurIPS 2020 Your GAN Is Secretly an Energy-Based Model and You Should Use Discriminator Driven Latent Sampling Tong Che, Ruixiang Zhang, Jascha Sohl-Dickstein, Hugo Larochelle, Liam Paull, Yuan Cao, Yoshua Bengio

ICLRW 2019 Perceptual Generative Autoencoders Zijun Zhang, Ruixiang Zhang, Zongpeng Li, Yoshua Bengio, Liam Paull

NeurIPS 2018 MetaGAN: An Adversarial Approach to Few-Shot Learning Ruixiang Zhang, Tong Che, Zoubin Ghahramani, Yoshua Bengio, Yangqiu Song