Raymond A. Yeh

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 59

Top Topics

Image Inpainting

Convolutional Neural Network

Reinforcement Learning

Diffusion Models

Top Venues

Publications

Md Ashiqur Rahman, Robert Joseph George, Mogab Elleithy, Daniel V. Leibovici, Zongyi Li, Boris Bonev, Colin White, Julius Berner, Raymond A. Yeh, Jean Kossaifi, Kamyar Azizzadenesheli, Anima Anandkumar
Pretraining Codomain Attention Neural Operators for Solving Multiphysics PDEs. CoRR (2024)
Jae Joong Lee, Bosheng Li, Sara Beery, Jonathan Huang, Songlin Fei, Raymond A. Yeh, Bedrich Benes
Tree-D Fusion: Simulation-Ready Tree Dataset from Single Images with Diffusion Priors. CoRR (2024)
Joshua Ahn, Haochen Wang, Raymond A. Yeh, Greg Shakhnarovich
Alpha Invariance: On Inverse Scaling Between Distance and Volume Density in Neural Radiance Fields. CoRR (2024)
Boheng Zhao, Rana Hanocka, Raymond A. Yeh
AmbiGen: Generating Ambigrams from Pre-trained Diffusion Model. CoRR (2023)
Md Ashiqur Rahman, Raymond A. Yeh
Truly Scale-Equivariant Deep Nets with Fourier Layers. NeurIPS (2023)
Chiao-An Yang, Meng-Lin Wu, Raymond A. Yeh, Yu-Chiang Frank Wang
Consistent and Multi-Scale Scene Graph Transformer for Semantic-Guided Image Outpainting. ICIP (2023)
Adnan Firoze, Cameron Wingren, Raymond A. Yeh, Bedrich Benes, Daniel G. Aliaga
Tree Instance Segmentation with Temporal Contour Graph. CVPR (2023)
Md Ashiqur Rahman, Raymond A. Yeh
Truly Scale-Equivariant Deep Nets with Fourier Layers. CoRR (2023)
Yijia Zheng, Raymond A. Yeh
IMMA: Immunizing text-to-image Models against Malicious Adaptation. CoRR (2023)
Renan A. Rojas-Gomez, Teck-Yian Lim, Minh N. Do, Raymond A. Yeh
Making Vision Transformers Truly Shift-Equivariant. CoRR (2023)
Yuan-Ting Hu, Alexander G. Schwing, Raymond A. Yeh
Surface Snapping Optimization Layer for Single Image Object Shape Reconstruction. ICML (2023)
Haochen Wang, Xiaodan Du, Jiahao Li, Raymond A. Yeh, Greg Shakhnarovich
Score Jacobian Chaining: Lifting Pretrained 2D Diffusion Models for 3D Generation. CVPR (2023)
Jiahao Li, Greg Shakhnarovich, Raymond A. Yeh
Adapting CLIP For Phrase Localization Without Further Training. CoRR (2022)
Renan A. Rojas-Gomez, Teck-Yian Lim, Alexander G. Schwing, Minh N. Do, Raymond A. Yeh
Learnable Polyphase Sampling for Shift Invariant and Equivariant Convolutional Networks. CoRR (2022)
Haochen Wang, Xiaodan Du, Jiahao Li, Raymond A. Yeh, Greg Shakhnarovich
Score Jacobian Chaining: Lifting Pretrained 2D Diffusion Models for 3D Generation. CoRR (2022)
Renan A. Rojas-Gomez, Teck-Yian Lim, Alexander G. Schwing, Minh N. Do, Raymond A. Yeh
Learnable Polyphase Sampling for Shift Invariant and Equivariant Convolutional Networks. NeurIPS (2022)
Renan A. Rojas-Gomez, Raymond A. Yeh, Minh N. Do, Anh Nguyen
Inverting Adversarially Robust Networks for Image Synthesis. ACCV (6) (2022)
Raymond A. Yeh, Yuan-Ting Hu, Mark Hasegawa-Johnson, Alexander G. Schwing
Equivariance Discovery by Learned Parameter-Sharing. CoRR (2022)
Xiaodan Du, Raymond A. Yeh, Nicholas I. Kolkin, Eli Shechtman, Greg Shakhnarovich
Text-Free Learning of a Natural Language Interface for Pretrained Face Generators. CoRR (2022)
Raymond A. Yeh, Yuan-Ting Hu, Zhongzheng Ren, Alexander G. Schwing
Total Variation Optimization Layers for Computer Vision. CoRR (2022)
Raymond A. Yeh, Yuan-Ting Hu, Zhongzheng Ren, Alexander G. Schwing
Total Variation Optimization Layers for Computer Vision. CVPR (2022)
William Gao, April Wang, Gal Metzer, Raymond A. Yeh, Rana Hanocka
TetGAN: A Convolutional Neural Network for Tetrahedral Mesh Generation. BMVC (2022)
Ofek Pearl, Itai Lang, Yuhua Hu, Raymond A. Yeh, Rana Hanocka
GeoCode: Interpretable Shape Programs. CoRR (2022)
Raymond A. Yeh, Yuan-Ting Hu, Mark Hasegawa-Johnson, Alexander G. Schwing
Equivariance Discovery by Learned Parameter-Sharing. AISTATS (2022)
William Gao, April Wang, Gal Metzer, Raymond A. Yeh, Rana Hanocka
TetGAN: A Convolutional Neural Network for Tetrahedral Mesh Generation. CoRR (2022)
Iou-Jen Liu, Zhongzheng Ren, Raymond A. Yeh, Alexander G. Schwing
Semantic Tracklets: An Object-Centric Representation for Visual Multi-Agent Reinforcement Learning. IROS (2021)
Qian Jiang, Xiaofan Zhang, Deming Chen, Minh N. Do, Raymond A. Yeh
EH-DNAS: End-to-End Hardware-aware Differentiable Neural Architecture Search. CoRR (2021)
Iou-Jen Liu, Zhongzheng Ren, Raymond A. Yeh, Alexander G. Schwing
Semantic Tracklets: An Object-Centric Representation for Visual Multi-Agent Reinforcement Learning. CoRR (2021)
Yuan-Ting Hu, Jiahong Wang, Raymond A. Yeh, Alexander G. Schwing
SAIL-VOS 3D: A Synthetic Dataset and Baselines for Object Detection and 3D Mesh Reconstruction from Video Data. CoRR (2021)
Yuan-Ting Hu, Jiahong Wang, Raymond A. Yeh, Alexander G. Schwing
SAIL-VOS 3D: A Synthetic Dataset and Baselines for Object Detection and 3D Mesh Reconstruction From Video Data. CVPR Workshops (2021)
Junzhe Zhu, Raymond A. Yeh, Mark Hasegawa-Johnson
Multi-Decoder Dprnn: Source Separation for Variable Number of Speakers. ICASSP (2021)
Yuan-Ting Hu, Jiahong Wang, Raymond A. Yeh, Alexander G. Schwing
SAIL-VOS 3D: A Synthetic Dataset and Baselines for Object Detection and 3D Mesh Reconstruction From Video Data. CVPR (2021)
Iou-Jen Liu, Unnat Jain, Raymond A. Yeh, Alexander G. Schwing
Cooperative Exploration for Multi-Agent Deep Reinforcement Learning. CoRR (2021)
Renan A. Rojas-Gomez, Raymond A. Yeh, Minh N. Do, Anh Nguyen
Inverting Adversarially Robust Networks for Image Synthesis. CoRR (2021)
Iou-Jen Liu, Unnat Jain, Raymond A. Yeh, Alexander G. Schwing
Cooperative Exploration for Multi-Agent Deep Reinforcement Learning. ICML (2021)
Zhongzheng Ren, Raymond A. Yeh, Alexander G. Schwing
Not All Unlabeled Data are Equal: Learning to Weight Data in Semi-supervised Learning. CoRR (2020)
Junzhe Zhu, Raymond A. Yeh, Mark Hasegawa-Johnson
Multi-Decoder DPRNN: High Accuracy Source Counting and Separation. CoRR (2020)
Zhongzheng Ren, Raymond A. Yeh, Alexander G. Schwing
Not All Unlabeled Data are Equal: Learning to Weight Data in Semi-supervised Learning. NeurIPS (2020)
Iou-Jen Liu, Raymond A. Yeh, Alexander G. Schwing
High-Throughput Synchronous Deep RL. NeurIPS (2020)
Iou-Jen Liu, Raymond A. Yeh, Alexander G. Schwing
High-Throughput Synchronous Deep RL. CoRR (2020)
Iou-Jen Liu, Raymond A. Yeh, Alexander G. Schwing
PIC: Permutation Invariant Critic for Multi-Agent Deep Reinforcement Learning. CoRL (2019)
Raymond A. Yeh, Yuan-Ting Hu, Alexander G. Schwing
Chirality Nets for Human Pose Regression. CoRR (2019)
Khoi-Nguyen C. Mac, Dhiraj Joshi, Raymond A. Yeh, Jinjun Xiong, Rogério Schmidt Feris, Minh N. Do
Learning Motion in Feature Space: Locally-Consistent Deformable Convolution Networks for Fine-Grained Action Detection. ICCV (2019)
Raymond A. Yeh, Yuan-Ting Hu, Alexander G. Schwing
Chirality Nets for Human Pose Regression. NeurIPS (2019)
Iou-Jen Liu, Raymond A. Yeh, Alexander G. Schwing
PIC: Permutation Invariant Critic for Multi-Agent Deep Reinforcement Learning. CoRR (2019)
Raymond A. Yeh, Alexander G. Schwing, Jonathan Huang, Kevin Murphy
Diverse Generation for Multi-Agent Sports Games. CVPR (2019)
Teck-Yian Lim, Raymond A. Yeh, Yijia Xu, Minh N. Do, Mark Hasegawa-Johnson
Time-Frequency Networks for Audio Super-Resolution. ICASSP (2018)
Raymond A. Yeh, Jinjun Xiong, Wen-mei W. Hwu, Minh N. Do, Alexander G. Schwing
Interpretable and Globally Optimal Prediction for Textual Grounding using Image Concepts. CoRR (2018)
Raymond A. Yeh, Minh N. Do, Alexander G. Schwing
Unsupervised Textual Grounding: Linking Words to Image Concepts. CVPR (2018)
Raymond A. Yeh, Teck-Yian Lim, Chen Chen, Alexander G. Schwing, Mark Hasegawa-Johnson, Minh N. Do
Image Restoration with Deep Generative Models. ICASSP (2018)
Raymond A. Yeh, Minh N. Do, Alexander G. Schwing
Unsupervised Textual Grounding: Linking Words to Image Concepts. CoRR (2018)
Khoi-Nguyen C. Mac, Dhiraj Joshi, Raymond A. Yeh, Jinjun Xiong, Rogério Schmidt Feris, Minh N. Do
Locally-Consistent Deformable Convolution Networks for Fine-Grained Action Detection. CoRR (2018)
Ziwei Liu, Raymond A. Yeh, Xiaoou Tang, Yiming Liu, Aseem Agarwala
Video Frame Synthesis Using Deep Voxel Flow. ICCV (2017)
Raymond A. Yeh, Jinjun Xiong, Wen-Mei W. Hwu, Minh N. Do, Alexander G. Schwing
Interpretable and Globally Optimal Prediction for Textual Grounding using Image Concepts. NIPS (2017)
Raymond A. Yeh, Chen Chen, Teck-Yian Lim, Alexander G. Schwing, Mark Hasegawa-Johnson, Minh N. Do
Semantic Image Inpainting with Deep Generative Models. CVPR (2017)
Ziwei Liu, Raymond A. Yeh, Xiaoou Tang, Yiming Liu, Aseem Agarwala
Video Frame Synthesis using Deep Voxel Flow. CoRR (2017)
Raymond A. Yeh, Chen Chen, Teck-Yian Lim, Mark Hasegawa-Johnson, Minh N. Do
Semantic Image Inpainting with Perceptual and Contextual Losses. CoRR (2016)
Raymond A. Yeh, Mark Hasegawa-Johnson, Minh N. Do
Stable and symmetric filter convolutional neural network. ICASSP (2016)
Raymond A. Yeh, Ziwei Liu, Dan B. Goldman, Aseem Agarwala
Semantic Facial Expression Editing using Autoencoded Flow. CoRR (2016)