Arash Vahdat

Publication Activity (10 Years)

Years Active: 2009-2024
Publications (10 Years): 86

Top Venues

CoRR

CVPR

NeurIPS

ICML

Publications

Dejia Xu, Weili Nie, Chao Liu, Sifei Liu, Jan Kautz, Zhangyang Wang, Arash Vahdat
CamCo: Camera-Controllable 3D-Consistent Image-to-Video Generation. CoRR (2024)
Dejia Xu, Ye Yuan, Morteza Mardani, Sifei Liu, Jiaming Song, Zhangyang Wang, Arash Vahdat
AGG: Amortized Generative 3D Gaussians for Single Image to 3D. CoRR (2024)
Omri Avrahami, Rinon Gal, Gal Chechik, Ohad Fried, Dani Lischinski, Arash Vahdat, Weili Nie
DiffUHaul: A Training-Free Method for Object Dragging in Images. CoRR (2024)
Yilun Xu, Gabriele Corso, Tommi S. Jaakkola, Arash Vahdat, Karsten Kreis
DisCo-Diff: Enhancing Continuous Diffusion Models with Discrete Latents. CoRR (2024)
Zhuoran Qiao, Weili Nie, Arash Vahdat, Thomas F. Miller III, Animashree Anandkumar
State-specific protein-ligand complex structure prediction with a multiscale deep generative model. Nat. Mac. Intell. 6 (2) (2024)
Siyi Gu, Minkai Xu, Alexander S. Powers, Weili Nie, Tomas Geffner, Karsten Kreis, Jure Leskovec, Arash Vahdat, Stefano Ermon
Aligning Target-Aware Molecule Diffusion Models with Exact Energy Optimization. CoRR (2024)
Hongkai Zheng, Weili Nie, Arash Vahdat, Anima Anandkumar
Fast Training of Diffusion Models with Masked Transformers. Trans. Mach. Learn. Res. 2024 (2024)
Weili Nie, Sifei Liu, Morteza Mardani, Chao Liu, Benjamin Eckart, Arash Vahdat
Compositional Text-to-Image Generation with Dense Blob Representations. CoRR (2024)
Morteza Mardani, Jiaming Song, Jan Kautz, Arash Vahdat
A Variational Perspective on Solving Inverse Problems with Diffusion Models. ICLR (2024)
Hongkai Zheng, Weili Nie, Arash Vahdat, Anima Anandkumar
Fast Training of Diffusion Models with Masked Transformers. CoRR (2023)
Ali Hatamizadeh, Jiaming Song, Guilin Liu, Jan Kautz, Arash Vahdat
DiffiT: Diffusion Vision Transformers for Image Generation. CoRR (2023)
Jiarui Xu, Sifei Liu, Arash Vahdat, Wonmin Byeon, Xiaolong Wang, Shalini De Mello
Open-Vocabulary Panoptic Segmentation with Text-to-Image Diffusion Models. CVPR (2023)
Morteza Mardani, Jiaming Song, Jan Kautz, Arash Vahdat
A Variational Perspective on Solving Inverse Problems with Diffusion Models. CoRR (2023)
Jiaming Song, Qinsheng Zhang, Hongxu Yin, Morteza Mardani, Ming-Yu Liu, Jan Kautz, Yongxin Chen, Arash Vahdat
Loss-Guided Diffusion Models for Plug-and-Play Controllable Generation. ICML (2023)
Paul Micaelli, Arash Vahdat, Hongxu Yin, Jan Kautz, Pavlo Molchanov
Recurrence without Recurrence: Stable Video Landmark Detection with Deep Equilibrium Models. CVPR (2023)
Hongkai Zheng, Weili Nie, Arash Vahdat, Kamyar Azizzadenesheli, Anima Anandkumar
Fast Sampling of Diffusion Models via Operator Learning. ICML (2023)
Jae Hyun Lim, Nikola B. Kovachki, Ricardo Baptista, Christopher Beckham, Kamyar Azizzadenesheli, Jean Kossaifi, Vikram Voleti, Jiaming Song, Karsten Kreis, Jan Kautz, Christopher Pal, Arash Vahdat, Anima Anandkumar
Score-based Diffusion Models in Function Space. CoRR (2023)
Maxim Zvyagin, Alexander Brace, Kyle Hippe, Yuntian Deng, Bin Zhang, Cindy Orozco Bohorquez, Austin Clyde, Bharat Kale, Danilo Perez-Rivera, Heng Ma, Carla M. Mann, Michael W. Irvin, Defne G. Ozgulbas, Natalia Vassilieva, J. Gregory Pauloski, Logan Ward, Valerie Hayot-Sasson, Murali Emani, Sam Foreman, Zhen Xie, Diangen Lin, Maulik Shukla, Weili Nie, Josh Romero, Christian Dallago, Arash Vahdat, Chaowei Xiao, Thomas Gibbs, Ian T. Foster, James J. Davis, Michael E. Papka, Thomas S. Brettin, Rick Stevens, Anima Anandkumar, Venkatram Vishwanath, Arvind Ramanathan
GenSLMs: Genome-scale language models reveal SARS-CoV-2 evolutionary dynamics. Int. J. High Perform. Comput. Appl. 37 (6) (2023)
Guan-Horng Liu, Arash Vahdat, De-An Huang, Evangelos A. Theodorou, Weili Nie, Anima Anandkumar
SB: Image-to-Image Schrödinger Bridge. ICML (2023)
Ye Yuan, Jiaming Song, Umar Iqbal, Arash Vahdat, Jan Kautz
PhysDiff: Physics-Guided Human Motion Diffusion Model. ICCV (2023)
Guan-Horng Liu, Arash Vahdat, De-An Huang, Evangelos A. Theodorou, Weili Nie, Anima Anandkumar
SB: Image-to-Image Schrödinger Bridge. CoRR (2023)
Jiaming Song, Arash Vahdat, Morteza Mardani, Jan Kautz
Pseudoinverse-Guided Diffusion Models for Inverse Problems. ICLR (2023)
Morteza Mardani, Noah D. Brenowitz, Yair Cohen, Jaideep Pathak, Chieh-Yu Chen, Cheng-Chin Liu, Arash Vahdat, Karthik Kashinath, Jan Kautz, Mike Pritchard
Generative Residual Diffusion Modeling for Km-scale Atmospheric Downscaling. CoRR (2023)
Jiarui Xu, Sifei Liu, Arash Vahdat, Wonmin Byeon, Xiaolong Wang, Shalini De Mello
Open-Vocabulary Panoptic Segmentation with Text-to-Image Diffusion Models. CoRR (2023)
Yuji Roh, Weili Nie, De-An Huang, Steven Euijong Whang, Arash Vahdat, Anima Anandkumar
Dr-Fairness: Dynamic Data Ratio Adjustment for Fair Training on Real and Generated Data. Trans. Mach. Learn. Res. 2023 (2023)
Paul Micaelli, Arash Vahdat, Hongxu Yin, Jan Kautz, Pavlo Molchanov
Recurrence without Recurrence: Stable Video Landmark Detection with Deep Equilibrium Models. CoRR (2023)
Shuaiwen Leon Song, Bonnie Kruft, Minjia Zhang, Conglong Li, Shiyang Chen, Chengming Zhang, Masahiro Tanaka, Xiaoxia Wu, Jeff Rasley, Ammar Ahmad Awan, Connor Holmes, Martin Cai, Adam Ghanem, Zhongzhu Zhou, Yuxiong He, Pete Luferenko, Divya Kumar, Jonathan A. Weyn, Ruixiong Zhang, Sylwester Klocek, Volodymyr Vragov, Mohammed AlQuraishi, Gustaf Ahdritz, Christina Floristean, Cristina Negri, Rao Kotamarthi, Venkatram Vishwanath, Arvind Ramanathan, Sam Foreman, Kyle Hippe, Troy Arcomano, Romit Maulik, Maxim Zvyagin, Alexander Brace, Bin Zhang, Cindy Orozco Bohorquez, Austin Clyde, Bharat Kale, Danilo Perez-Rivera, Heng Ma, Carla M. Mann, Michael W. Irvin, J. Gregory Pauloski, Logan T. Ward, Valérie Hayot-Sasson, Murali Emani, Zhen Xie, Diangen Lin, Maulik Shukla, Ian T. Foster, James J. Davis, Michael E. Papka, Thomas S. Brettin, Prasanna Balaprakash, Gina Tourassi, John Gounley, Heidi A. Hanson, Thomas E. Potok, Massimiliano Lupo Pasini, Kate Evans, Dan Lu, Dalton D. Lunga, Junqi Yin, Sajal Dash, Feiyi Wang, Mallikarjun Shankar, Isaac Lyngaas, Xiao Wang, Guojing Cong, Pei Zhang, Ming Fan, Siyan Liu, Adolfy Hoisie, Shinjae Yoo, Yihui Ren, William Tang, Kyle Felker, Alexey Svyatkovskiy, Hang Liu, Ashwin M. Aji, Angela Dalton, Michael J. Schulte, Karl Schulz, Yuntian Deng, Weili Nie, Josh Romero, Christian Dallago, Arash Vahdat, Chaowei Xiao, Thomas Gibbs, Anima Anandkumar, Rick Stevens
DeepSpeed4Science Initiative: Enabling Large-Scale Scientific Discovery through Sophisticated AI System Technologies. CoRR (2023)
Tim Dockhorn, Tianshi Cao, Arash Vahdat, Karsten Kreis
Differentially Private Diffusion Models. Trans. Mach. Learn. Res. 2023 (2023)
Sina Mohseni, Arash Vahdat, Jay Yadawa
Shifting Transformation Learning for Robust Out-of-Distribution Detection. BMVC (2022)
Tim Dockhorn, Tianshi Cao, Arash Vahdat, Karsten Kreis
Differentially Private Diffusion Models. CoRR (2022)
Weili Nie, Brandon Guo, Yujia Huang, Chaowei Xiao, Arash Vahdat, Anima Anandkumar
Diffusion Models for Adversarial Purification. CoRR (2022)
Xiaohui Zeng, Arash Vahdat, Francis Williams, Zan Gojcic, Or Litany, Sanja Fidler, Karsten Kreis
LION: Latent Point Diffusion Models for 3D Shape Generation. NeurIPS (2022)
Hongxu Yin, Arash Vahdat, Jose M. Alvarez, Arun Mallya, Jan Kautz, Pavlo Molchanov
A-ViT: Adaptive Tokens for Efficient Vision Transformer. CVPR (2022)
Ye Yuan, Jiaming Song, Umar Iqbal, Arash Vahdat, Jan Kautz
PhysDiff: Physics-Guided Human Motion Diffusion Model. CoRR (2022)
Hongkai Zheng, Weili Nie, Arash Vahdat, Kamyar Azizzadenesheli, Anima Anandkumar
Fast Sampling of Diffusion Models via Operator Learning. CoRR (2022)
Tim Dockhorn, Arash Vahdat, Karsten Kreis
GENIE: Higher-Order Denoising Diffusion Solvers. CoRR (2022)
Xiaohui Zeng, Arash Vahdat, Francis Williams, Zan Gojcic, Or Litany, Sanja Fidler, Karsten Kreis
LION: Latent Point Diffusion Models for 3D Shape Generation. CoRR (2022)
Zhuoran Qiao, Weili Nie, Arash Vahdat, Thomas F. Miller III, Anima Anandkumar
Dynamic-Backbone Protein-Ligand Structure Prediction with Multiscale Generative Diffusion Models. CoRR (2022)
Weili Nie, Brandon Guo, Yujia Huang, Chaowei Xiao, Arash Vahdat, Animashree Anandkumar
Diffusion Models for Adversarial Purification. ICML (2022)
Yogesh Balaji, Seungjun Nah, Xun Huang, Arash Vahdat, Jiaming Song, Karsten Kreis, Miika Aittala, Timo Aila, Samuli Laine, Bryan Catanzaro, Tero Karras, Ming-Yu Liu
eDiff-I: Text-to-Image Diffusion Models with an Ensemble of Expert Denoisers. CoRR (2022)
Tim Dockhorn, Arash Vahdat, Karsten Kreis
Score-Based Generative Modeling with Critically-Damped Langevin Diffusion. ICLR (2022)
Pavlo Molchanov, Jimmy Hall, Hongxu Yin, Jan Kautz, Nicolò Fusi, Arash Vahdat
LANA: Latency Aware Network Acceleration. ECCV (12) (2022)
Tim Dockhorn, Arash Vahdat, Karsten Kreis
GENIE: Higher-Order Denoising Diffusion Solvers. NeurIPS (2022)
Zhisheng Xiao, Karsten Kreis, Arash Vahdat
Tackling the Generative Learning Trilemma with Denoising Diffusion GANs. ICLR (2022)
Sina Mohseni, Arash Vahdat, Jay Yadawa
Multi-task Transformation Learning for Robust Out-of-Distribution Detection. CoRR (2021)
Arash Vahdat, Karsten Kreis, Jan Kautz
Score-based Generative Modeling in Latent Space. CoRR (2021)
Jyoti Aneja, Alexander G. Schwing, Jan Kautz, Arash Vahdat
A Contrastive Learning Approach for Training Variational Autoencoder Priors. NeurIPS (2021)
Weili Nie, Arash Vahdat, Anima Anandkumar
Controllable and Compositional Generation with Latent-Space Energy-Based Models. CoRR (2021)
Hongxu Yin, Arun Mallya, Arash Vahdat, Jose M. Alvarez, Jan Kautz, Pavlo Molchanov
See through Gradients: Image Batch Recovery via GradInversion. CoRR (2021)
Pavlo Molchanov, Jimmy Hall, Hongxu Yin, Jan Kautz, Nicolò Fusi, Arash Vahdat
HANT: Hardware-Aware Network Transformation. CoRR (2021)
Hongxu Yin, Arun Mallya, Arash Vahdat, Jose M. Alvarez, Jan Kautz, Pavlo Molchanov
See Through Gradients: Image Batch Recovery via GradInversion. CVPR (2021)
Hongxu Yin, Arash Vahdat, Jose M. Alvarez, Arun Mallya, Jan Kautz, Pavlo Molchanov
AdaViT: Adaptive Tokens for Efficient Vision Transformer. CoRR (2021)
Tim Dockhorn, Arash Vahdat, Karsten Kreis
Score-Based Generative Modeling with Critically-Damped Langevin Diffusion. CoRR (2021)
Weili Nie, Arash Vahdat, Anima Anandkumar
Controllable and Compositional Generation with Latent-Space Energy-Based Models. NeurIPS (2021)
Arash Vahdat, Karsten Kreis, Jan Kautz
Score-based Generative Modeling in Latent Space. NeurIPS (2021)
Zhisheng Xiao, Karsten Kreis, Arash Vahdat
Tackling the Generative Learning Trilemma with Denoising Diffusion GANs. CoRR (2021)
Zhisheng Xiao, Karsten Kreis, Jan Kautz, Arash Vahdat
VAEBM: A Symbiosis between Variational Autoencoders and Energy-based Models. ICLR (2021)
Tianshi Cao, Alex Bie, Arash Vahdat, Sanja Fidler, Karsten Kreis
Don't Generate Me: Training Differentially Private Generative Models with Sinkhorn Divergence. CoRR (2021)
Tianshi Cao, Alex Bie, Arash Vahdat, Sanja Fidler, Karsten Kreis
Don't Generate Me: Training Differentially Private Generative Models with Sinkhorn Divergence. NeurIPS (2021)
Jyoti Aneja, Alexander G. Schwing, Jan Kautz, Arash Vahdat
NCP-VAE: Variational Autoencoders with Noise Contrastive Priors. CoRR (2020)
Mostafa S. Ibrahim, Arash Vahdat, Mani Ranjbar, William G. Macready
Semi-Supervised Semantic Image Segmentation With Self-Correcting Networks. CVPR (2020)
Tanmay Gupta, Arash Vahdat, Gal Chechik, Xiaodong Yang, Jan Kautz, Derek Hoiem
Contrastive Learning for Weakly Supervised Phrase Grounding. ECCV (3) (2020)
Arash Vahdat, Evgeny Andriyash, William G. Macready
Undirected Graphical Models as Approximate Posteriors. ICML (2020)
Jeremy Bernstein, Arash Vahdat, Yisong Yue, Ming-Yu Liu
On the distance between two neural networks and the stability of learning. CoRR (2020)
Arash Vahdat, Jan Kautz
NVAE: A Deep Hierarchical Variational Autoencoder. NeurIPS (2020)
Jeremy Bernstein, Arash Vahdat, Yisong Yue, Ming-Yu Liu
On the distance between two neural networks and the stability of learning. NeurIPS (2020)
Zhisheng Xiao, Karsten Kreis, Jan Kautz, Arash Vahdat
VAEBM: A Symbiosis between Variational Autoencoders and Energy-based Models. CoRR (2020)
Tanmay Gupta, Arash Vahdat, Gal Chechik, Xiaodong Yang, Jan Kautz, Derek Hoiem
Contrastive Learning for Weakly Supervised Phrase Grounding. CoRR (2020)
Arash Vahdat, Arun Mallya, Ming-Yu Liu, Jan Kautz
UNAS: Differentiable Architecture Search Meets Reinforcement Learning. CVPR (2020)
Arash Vahdat, Jan Kautz
NVAE: A Deep Hierarchical Variational Autoencoder. CoRR (2020)
Arash Vahdat, Evgeny Andriyash, William G. Macready
Learning Undirected Posteriors by Backpropagation through MCMC Updates. CoRR (2019)
Arash Vahdat, Arun Mallya, Ming-Yu Liu, Jan Kautz
UNAS: Differentiable Architecture Search Meets Reinforcement Learning. CoRR (2019)
Mehran Khodabandeh, Arash Vahdat, Mani Ranjbar, William G. Macready
A Robust Learning Approach to Domain Adaptive Object Detection. CoRR (2019)
Mehran Khodabandeh, Arash Vahdat, Mani Ranjbar, William G. Macready
A Robust Learning Approach to Domain Adaptive Object Detection. ICCV (2019)
Mostafa S. Ibrahim, Arash Vahdat, William G. Macready
Weakly Supervised Semantic Image Segmentation with Self-correcting Networks. CoRR (2018)
Arash Vahdat, William G. Macready, Zhengbing Bian, Amir Khoshaman, Evgeny Andriyash
DVAE++: Discrete Variational Autoencoders with Overlapping Transformations. ICML (2018)
Arash Vahdat, Evgeny Andriyash, William G. Macready
DVAE#: Discrete Variational Autoencoders with Relaxed Boltzmann Priors. CoRR (2018)
Arash Vahdat, Evgeny Andriyash, William G. Macready
DVAE#: Discrete Variational Autoencoders with Relaxed Boltzmann Priors. NeurIPS (2018)
Arash Vahdat, William G. Macready, Zhengbing Bian, Amir Khoshaman
DVAE++: Discrete Variational Autoencoders with Overlapping Transformations. CoRR (2018)
Evgeny Andriyash, Arash Vahdat, William G. Macready
Improved Gradient-Based Optimization Over Discrete Distributions. CoRR (2018)
Arash Vahdat
Toward Robustness against Label Noise in Training Deep Discriminative Neural Networks. NIPS (2017)
Arash Vahdat
Toward Robustness against Label Noise in Training Deep Discriminative Neural Networks. CoRR (2017)
Zhiwei Deng, Arash Vahdat, Hexiang Hu, Greg Mori
Structure Inference Machines: Recurrent Neural Networks for Analyzing Relations in Group Activity Recognition. CVPR (2016)
Mostafa S. Ibrahim, Srikanth Muralidharan, Zhiwei Deng, Arash Vahdat, Greg Mori
Hierarchical Deep Temporal Models for Group Activity Recognition. CoRR (2016)
Mehran Khodabandeh, Srikanth Muralidharan, Arash Vahdat, Nazanin Mehrasa, Eduardo M. Pereira, Shin'ichi Satoh, Greg Mori
Unsupervised learning of supervoxel embeddings for video Segmentation. ICPR (2016)
Mostafa S. Ibrahim, Srikanth Muralidharan, Zhiwei Deng, Arash Vahdat, Greg Mori
A Hierarchical Deep Temporal Model for Group Activity Recognition. CVPR (2016)
Mostafa S. Ibrahim, Srikanth Muralidharan, Zhiwei Deng, Arash Vahdat, Greg Mori
A Hierarchical Deep Temporal Model for Group Activity Recognition. CoRR (2015)
Zhiwei Deng, Arash Vahdat, Hexiang Hu, Greg Mori
Structure Inference Machines: Recurrent Neural Networks for Analyzing Relations in Group Activity Recognition. CoRR (2015)
Hossein Hajimirsadeghi, Wang Yan, Arash Vahdat, Greg Mori
Visual Recognition by Counting Instances: A Multi-Instance Cardinality Potential Kernel. CoRR (2015)
Yasaman S. Sefidgar, Arash Vahdat, Stephen Se, Greg Mori
Discriminative key-component models for interaction detection and recognition. Comput. Vis. Image Underst. 135 (2015)
Hossein Hajimirsadeghi, Wang Yan, Arash Vahdat, Greg Mori
Visual recognition by counting instances: A multi-instance cardinality potential kernel. CVPR (2015)
Mehran Khodabandeh, Arash Vahdat, Guang-Tong Zhou, Hossein Hajimirsadeghi, Mehrsan Javan Roshtkhari, Greg Mori, Stephen Se
Discovering Human Interactions in Videos with Limited Data Labeling. CoRR (2015)
Mehran Khodabandeh, Arash Vahdat, Guang-Tong Zhou, Hossein Hajimirsadeghi, Mehrsan Javan Roshtkhari, Greg Mori, Stephen Se
Discovering human interactions in videos with limited data labeling. CVPR Workshops (2015)
Arash Vahdat, Guang-Tong Zhou, Greg Mori
Discovering Video Clusters from Visual Features and Noisy Tags. ECCV (6) (2014)
Sangmin Oh, Scott McCloskey, Ilseo Kim, Arash Vahdat, Kevin J. Cannons, Hossein Hajimirsadeghi, Greg Mori, A. G. Amitha Perera, Megha Pandey, Jason J. Corso
Multimedia event detection with multimodal feature fusion and temporal concept localization. Mach. Vis. Appl. 25 (1) (2014)
Sangmin Oh, A. G. Amitha Perera, Ilseo Kim, Megha Pandey, Kevin J. Cannons, Hossein Hajimirsadeghi, Arash Vahdat, Greg Mori, Ben Miller, Scott McCloskey, You-Chi Cheng, Zhen Huang, Chin-Hui Lee, Chenliang Xu, Rohit Kumar, Wei Chen, Jason J. Corso, Li Fei-Fei, Daphne Koller, Vignesh Ramanathan, Kevin Tang, Armand Joulin, Alexandre Alahi
TRECVID 2013 GENIE: Multimedia Event Detection and Recounting. TRECVID (2013)
Arash Vahdat, Greg Mori
Handling Uncertain Tags in Visual Recognition. ICCV (2013)
Arash Vahdat, Kevin J. Cannons, Greg Mori, Sangmin Oh, Ilseo Kim
Compositional Models for Video Event Detection: A Multiple Kernel Learning Latent Variable Approach. ICCV (2013)
Guang-Tong Zhou, Tian Lan, Arash Vahdat, Greg Mori
Latent Maximum Margin Clustering. NIPS (2013)
Ilseo Kim, Sangmin Oh, Arash Vahdat, Kevin J. Cannons, A. G. Amitha Perera, Greg Mori
Segmental multi-way local pooling for video recognition. ACM Multimedia (2013)

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Publication Activity (10 Years)

Top Topics

Top Venues

Arash Vahdat