Arash Vahdat

According to our database, Arash Vahdat authored at least 74 papers between 2009 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of three.

2024

AGG: Amortized Generative 3D Gaussians for Single Image to 3D.

Dejia Xu, Ye Yuan, Morteza Mardani, Sifei Liu, Jiaming Song, Zhangyang Wang, Arash Vahdat

CoRR, 2024

2023

NeuralPLexer evaluation datasets and predictions.

Zhuoran Qiao, Weili Nie, Arash Vahdat, Thomas F. Miller III, Animashree Anandkumar

Dataset, December, 2023

GenSLMs: Genome-scale language models reveal SARS-CoV-2 evolutionary dynamics.

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 T. Ward, Valérie 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

Int. J. High Perform. Comput. Appl., November, 2023

DiffiT: Diffusion Vision Transformers for Image Generation.

Ali Hatamizadeh, Jiaming Song, Guilin Liu, Jan Kautz, Arash Vahdat

CoRR, 2023

DeepSpeed4Science Initiative: Enabling Large-Scale Scientific Discovery through Sophisticated AI System Technologies.

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

CoRR, 2023

Generative Residual Diffusion Modeling for Km-scale Atmospheric Downscaling.

Morteza Mardani, Noah D. Brenowitz, Yair Cohen, Jaideep Pathak, Chieh-Yu Chen, Cheng-Chin Liu, Arash Vahdat, Karthik Kashinath, Jan Kautz, Mike Pritchard

CoRR, 2023

Fast Training of Diffusion Models with Masked Transformers.

Hongkai Zheng, Weili Nie, Arash Vahdat, Anima Anandkumar

CoRR, 2023

A Variational Perspective on Solving Inverse Problems with Diffusion Models.

Morteza Mardani, Jiaming Song, Jan Kautz, Arash Vahdat

CoRR, 2023

Score-based Diffusion Models in Function Space.

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

CoRR, 2023

Fast Sampling of Diffusion Models via Operator Learning.

Hongkai Zheng, Weili Nie, Arash Vahdat, Kamyar Azizzadenesheli, Anima Anandkumar

Proceedings of the International Conference on Machine Learning, 2023

Loss-Guided Diffusion Models for Plug-and-Play Controllable Generation.

Jiaming Song, Qinsheng Zhang, Hongxu Yin, Morteza Mardani, Ming-Yu Liu, Jan Kautz, Yongxin Chen, Arash Vahdat

Proceedings of the International Conference on Machine Learning, 2023

I²SB: Image-to-Image Schrödinger Bridge.

Guan-Horng Liu, Arash Vahdat, De-An Huang, Evangelos A. Theodorou, Weili Nie, Anima Anandkumar

Proceedings of the International Conference on Machine Learning, 2023

Pseudoinverse-Guided Diffusion Models for Inverse Problems.

Jiaming Song, Arash Vahdat, Morteza Mardani, Jan Kautz

Proceedings of the Eleventh International Conference on Learning Representations, 2023

PhysDiff: Physics-Guided Human Motion Diffusion Model.

Ye Yuan, Jiaming Song, Umar Iqbal, Arash Vahdat, Jan Kautz

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Open-Vocabulary Panoptic Segmentation with Text-to-Image Diffusion Models.

Jiarui Xu, Sifei Liu, Arash Vahdat, Wonmin Byeon, Xiaolong Wang, Shalini De Mello

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Recurrence without Recurrence: Stable Video Landmark Detection with Deep Equilibrium Models.

Paul Micaelli, Arash Vahdat, Hongxu Yin, Jan Kautz, Pavlo Molchanov

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

eDiff-I: Text-to-Image Diffusion Models with an Ensemble of Expert Denoisers.

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

CoRR, 2022

Differentially Private Diffusion Models.

Tim Dockhorn, Tianshi Cao, Arash Vahdat, Karsten Kreis

CoRR, 2022

Dynamic-Backbone Protein-Ligand Structure Prediction with Multiscale Generative Diffusion Models.

Zhuoran Qiao, Weili Nie, Arash Vahdat, Thomas F. Miller III, Anima Anandkumar

CoRR, 2022

LION: Latent Point Diffusion Models for 3D Shape Generation.

Xiaohui Zeng, Arash Vahdat, Francis Williams, Zan Gojcic, Or Litany, Sanja Fidler, Karsten Kreis

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

GENIE: Higher-Order Denoising Diffusion Solvers.

Tim Dockhorn, Arash Vahdat, Karsten Kreis

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Diffusion Models for Adversarial Purification.

Weili Nie, Brandon Guo, Yujia Huang, Chaowei Xiao, Arash Vahdat, Animashree Anandkumar

Proceedings of the International Conference on Machine Learning, 2022

Tackling the Generative Learning Trilemma with Denoising Diffusion GANs.

Zhisheng Xiao, Karsten Kreis, Arash Vahdat

Proceedings of the Tenth International Conference on Learning Representations, 2022

Score-Based Generative Modeling with Critically-Damped Langevin Diffusion.

Tim Dockhorn, Arash Vahdat, Karsten Kreis

Proceedings of the Tenth International Conference on Learning Representations, 2022

LANA: Latency Aware Network Acceleration.

Pavlo Molchanov, Jimmy Hall, Hongxu Yin, Jan Kautz, Nicolò Fusi, Arash Vahdat

Proceedings of the Computer Vision - ECCV 2022, 2022

A-ViT: Adaptive Tokens for Efficient Vision Transformer.

Hongxu Yin, Arash Vahdat, José M. Álvarez, Arun Mallya, Jan Kautz, Pavlo Molchanov

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Shifting Transformation Learning for Robust Out-of-Distribution Detection.

Sina Mohseni, Arash Vahdat, Jay Yadawa

Proceedings of the 33rd British Machine Vision Conference 2022, 2022

2021

AdaViT: Adaptive Tokens for Efficient Vision Transformer.

Hongxu Yin, Arash Vahdat, José M. Álvarez, Arun Mallya, Jan Kautz, Pavlo Molchanov

CoRR, 2021

HANT: Hardware-Aware Network Transformation.

Pavlo Molchanov, Jimmy Hall, Hongxu Yin, Jan Kautz, Nicolò Fusi, Arash Vahdat

CoRR, 2021

Multi-task Transformation Learning for Robust Out-of-Distribution Detection.

Sina Mohseni, Arash Vahdat, Jay Yadawa

CoRR, 2021

Score-based Generative Modeling in Latent Space.

Arash Vahdat, Karsten Kreis, Jan Kautz

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Controllable and Compositional Generation with Latent-Space Energy-Based Models.

Weili Nie, Arash Vahdat, Anima Anandkumar

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Don't Generate Me: Training Differentially Private Generative Models with Sinkhorn Divergence.

Tianshi Cao, Alex Bie, Arash Vahdat, Sanja Fidler, Karsten Kreis

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

A Contrastive Learning Approach for Training Variational Autoencoder Priors.

Jyoti Aneja, Alexander G. Schwing, Jan Kautz, Arash Vahdat

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

VAEBM: A Symbiosis between Variational Autoencoders and Energy-based Models.

Zhisheng Xiao, Karsten Kreis, Jan Kautz, Arash Vahdat

Proceedings of the 9th International Conference on Learning Representations, 2021

See Through Gradients: Image Batch Recovery via GradInversion.

Hongxu Yin, Arun Mallya, Arash Vahdat, José M. Álvarez, Jan Kautz, Pavlo Molchanov

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2020

NCP-VAE: Variational Autoencoders with Noise Contrastive Priors.

Jyoti Aneja, Alexander G. Schwing, Jan Kautz, Arash Vahdat

CoRR, 2020

NVAE: A Deep Hierarchical Variational Autoencoder.

Arash Vahdat, Jan Kautz

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

On the distance between two neural networks and the stability of learning.

Jeremy Bernstein, Arash Vahdat, Yisong Yue, Ming-Yu Liu

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Undirected Graphical Models as Approximate Posteriors.

Arash Vahdat, Evgeny Andriyash, William G. Macready

Proceedings of the 37th International Conference on Machine Learning, 2020

Contrastive Learning for Weakly Supervised Phrase Grounding.

Tanmay Gupta, Arash Vahdat, Gal Chechik, Xiaodong Yang, Jan Kautz, Derek Hoiem

Proceedings of the Computer Vision - ECCV 2020, 2020

UNAS: Differentiable Architecture Search Meets Reinforcement Learning.

Arash Vahdat, Arun Mallya, Ming-Yu Liu, Jan Kautz

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Semi-Supervised Semantic Image Segmentation With Self-Correcting Networks.

Mostafa S. Ibrahim, Arash Vahdat, Mani Ranjbar, William G. Macready

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019

Learning Undirected Posteriors by Backpropagation through MCMC Updates.

Arash Vahdat, Evgeny Andriyash, William G. Macready

CoRR, 2019

A Robust Learning Approach to Domain Adaptive Object Detection.

Mehran Khodabandeh, Arash Vahdat, Mani Ranjbar, William G. Macready

Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

2018

Weakly Supervised Semantic Image Segmentation with Self-correcting Networks.

Mostafa S. Ibrahim, Arash Vahdat, William G. Macready

CoRR, 2018

Improved Gradient-Based Optimization Over Discrete Distributions.

Evgeny Andriyash, Arash Vahdat, William G. Macready

CoRR, 2018

DVAE++: Discrete Variational Autoencoders with Overlapping Transformations.

Arash Vahdat, William G. Macready, Zhengbing Bian, Amir Khoshaman

CoRR, 2018

DVAE#: Discrete Variational Autoencoders with Relaxed Boltzmann Priors.

Arash Vahdat, Evgeny Andriyash, William G. Macready

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

DVAE++: Discrete Variational Autoencoders with Overlapping Transformations.

Arash Vahdat, William G. Macready, Zhengbing Bian, Amir Khoshaman, Evgeny Andriyash

Proceedings of the 35th International Conference on Machine Learning, 2018

2017

Toward Robustness against Label Noise in Training Deep Discriminative Neural Networks.

Arash Vahdat

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

2016

Hierarchical Deep Temporal Models for Group Activity Recognition.

Mostafa S. Ibrahim, Srikanth Muralidharan, Zhiwei Deng, Arash Vahdat, Greg Mori

CoRR, 2016

Unsupervised learning of supervoxel embeddings for video Segmentation.

Mehran Khodabandeh, Srikanth Muralidharan, Arash Vahdat, Nazanin Mehrasa, Eduardo M. Pereira, Shin'ichi Satoh, Greg Mori

Proceedings of the 23rd International Conference on Pattern Recognition, 2016

A Hierarchical Deep Temporal Model for Group Activity Recognition.

Mostafa S. Ibrahim, Srikanth Muralidharan, Zhiwei Deng, Arash Vahdat, Greg Mori

Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition, 2016

Structure Inference Machines: Recurrent Neural Networks for Analyzing Relations in Group Activity Recognition.

Zhiwei Deng, Arash Vahdat, Hexiang Hu, Greg Mori

Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition, 2016

2015

Discriminative key-component models for interaction detection and recognition.

Yasaman S. Sefidgar, Arash Vahdat, Stephen Se, Greg Mori

Comput. Vis. Image Underst., 2015

Discovering human interactions in videos with limited data labeling.

Mehran Khodabandeh, Arash Vahdat, Guang-Tong Zhou, Hossein Hajimirsadeghi, Mehrsan Javan Roshtkhari, Greg Mori, Stephen Se

Proceedings of the 2015 IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2015

Visual recognition by counting instances: A multi-instance cardinality potential kernel.

Hossein Hajimirsadeghi, Wang Yan, Arash Vahdat, Greg Mori

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015

2014

Multimedia event detection with multimodal feature fusion and temporal concept localization.

Sangmin Oh, Scott McCloskey, Ilseo Kim, Arash Vahdat, Kevin J. Cannons, Hossein Hajimirsadeghi, Greg Mori, A. G. Amitha Perera, Megha Pandey, Jason J. Corso

Mach. Vis. Appl., 2014

Discovering Video Clusters from Visual Features and Noisy Tags.

Arash Vahdat, Guang-Tong Zhou, Greg Mori

Proceedings of the Computer Vision - ECCV 2014, 2014

2013

TRECVID 2013 GENIE: Multimedia Event Detection and Recounting.

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

Proceedings of the 2013 TREC Video Retrieval Evaluation, 2013

Latent Maximum Margin Clustering.

Guang-Tong Zhou, Tian Lan, Arash Vahdat, Greg Mori

Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Segmental multi-way local pooling for video recognition.

Ilseo Kim, Sangmin Oh, Arash Vahdat, Kevin J. Cannons, A. G. Amitha Perera, Greg Mori

Proceedings of the ACM Multimedia Conference, 2013

Handling Uncertain Tags in Visual Recognition.

Arash Vahdat, Greg Mori

Proceedings of the IEEE International Conference on Computer Vision, 2013

Compositional Models for Video Event Detection: A Multiple Kernel Learning Latent Variable Approach.

Arash Vahdat, Kevin J. Cannons, Greg Mori, Sangmin Oh, Ilseo Kim

Proceedings of the IEEE International Conference on Computer Vision, 2013

2012

TRECVID 2012 GENIE: Multimedia Event Detection and Recounting.

A. G. Amitha Perera, Sangmin Oh, Megha Pandey, Tianyang Ma, Anthony Hoogs, Arash Vahdat, Kevin J. Cannons, Hossein Hajimirsadeghi, Greg Mori, Scott McCloskey, Ben Miller, Sharath Venkatesha, Pedro Davalos, Pradipto Das, Chenliang Xu, Jason J. Corso, Rohini K. Srihari, Ilseo Kim, You-Chi Cheng, Zhen Huang, Chin-Hui Lee, Kevin Tang, Li Fei-Fei, Daphne Koller

Proceedings of the 2012 TREC Video Retrieval Evaluation, 2012

Kernel Latent SVM for Visual Recognition.

Weilong Yang, Yang Wang, Arash Vahdat, Greg Mori

Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Similarity Constrained Latent Support Vector Machine: An Application to Weakly Supervised Action Classification.

Nataliya Shapovalova, Arash Vahdat, Kevin J. Cannons, Tian Lan, Greg Mori

Proceedings of the Computer Vision - ECCV 2012, 2012

Complex loss optimization via dual decomposition.

Mani Ranjbar, Arash Vahdat, Greg Mori

Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition, 2012

2011

GENIE TRECVID 2011 Multimedia Event Detection: Late-Fusion Approaches to Combine Multiple Audio-Visual features.

A. G. Amitha Perera, Sangmin Oh, Matthew J. Leotta, Ilseo Kim, Byungki Byun, Chin-Hui Lee, Scott McCloskey, Jingchen Liu, Ben Miller, Zhi Feng Huang, Arash Vahdat, Weilong Yang, Greg Mori, Kevin Tang, Daphne Koller, Li Fei-Fei, Kang Li, Gang Chen, Jason J. Corso, Yun Fu, Rohini K. Srihari

Proceedings of the 2011 TREC Video Retrieval Evaluation, 2011

A discriminative key pose sequence model for recognizing human interactions.

Arash Vahdat, Bo Gao, Mani Ranjbar, Greg Mori

Proceedings of the IEEE International Conference on Computer Vision Workshops, 2011

2010

Generalized Sparse Classifiers for Decoding Cognitive States in fMRI.

Bernard Ng, Arash Vahdat, Ghassan Hamarneh, Rafeef Abugharbieh

Proceedings of the Machine Learning in Medical Imaging, First International Workshop, 2010

Colour From Grey by Optimized Colour Ordering.

Arash Vahdat, Mark S. Drew

Proceedings of the 18th Color and Imaging Conference, 2010

2009

Face virtual pose generation using aligned locally linear regression for face recognition.

Mohammad H. Rohban, Hamid R. Rabiee, Arash Vahdat

Proceedings of the International Conference on Image Processing, 2009