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2020 – today
- 2024
[j7]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): 195-208 (2024)- [j6]Hongkai Zheng, Weili Nie, Arash Vahdat, Anima Anandkumar:
Fast Training of Diffusion Models with Masked Transformers. Trans. Mach. Learn. Res. 2024 (2024) - [c54]Morteza Mardani, Jiaming Song, Jan Kautz, Arash Vahdat:
A Variational Perspective on Solving Inverse Problems with Diffusion Models. ICLR 2024 - [c53]Weili Nie, Sifei Liu, Morteza Mardani, Chao Liu, Benjamin Eckart, Arash Vahdat:
Compositional Text-to-Image Generation with Dense Blob Representations. ICML 2024 - [c52]Yilun Xu, Gabriele Corso, Tommi S. Jaakkola, Arash Vahdat, Karsten Kreis:
DisCo-Diff: Enhancing Continuous Diffusion Models with Discrete Latents. ICML 2024 - [i52]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 abs/2401.04099 (2024) - [i51]Weili Nie, Sifei Liu, Morteza Mardani, Chao Liu, Benjamin Eckart, Arash Vahdat:
Compositional Text-to-Image Generation with Dense Blob Representations. CoRR abs/2405.08246 (2024) - [i50]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 abs/2406.01594 (2024) - [i49]Dejia Xu, Weili Nie, Chao Liu, Sifei Liu, Jan Kautz, Zhangyang Wang, Arash Vahdat:
CamCo: Camera-Controllable 3D-Consistent Image-to-Video Generation. CoRR abs/2406.02509 (2024) - [i48]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 abs/2407.01648 (2024) - [i47]Yilun Xu, Gabriele Corso, Tommi S. Jaakkola, Arash Vahdat, Karsten Kreis:
DisCo-Diff: Enhancing Continuous Diffusion Models with Discrete Latents. CoRR abs/2407.03300 (2024) - [i46]Jaideep Pathak, Yair Cohen, Piyush Garg, Peter Harrington, Noah D. Brenowitz, Dale R. Durran, Morteza Mardani, Arash Vahdat, Shaoming Xu, Karthik Kashinath, Michael S. Pritchard:
Kilometer-Scale Convection Allowing Model Emulation using Generative Diffusion Modeling. CoRR abs/2408.10958 (2024) - [i45]Rohit Jena, Ali Taghibakhshi, Sahil Jain, Gerald Shen, Nima Tajbakhsh, Arash Vahdat:
Elucidating Optimal Reward-Diversity Tradeoffs in Text-to-Image Diffusion Models. CoRR abs/2409.06493 (2024) - 2023
- [j5]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:
GenSLMs: Genome-scale language models reveal SARS-CoV-2 evolutionary dynamics. Int. J. High Perform. Comput. Appl. 37(6): 683-705 (2023) - [j4]Tim Dockhorn, Tianshi Cao, Arash Vahdat, Karsten Kreis:
Differentially Private Diffusion Models. Trans. Mach. Learn. Res. 2023 (2023) - [j3]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) - [c51]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: 2955-2966 - [c50]Paul Micaelli, Arash Vahdat, Hongxu Yin, Jan Kautz, Pavlo Molchanov:
Recurrence without Recurrence: Stable Video Landmark Detection with Deep Equilibrium Models. CVPR 2023: 22814-22825 - [c49]Ye Yuan, Jiaming Song, Umar Iqbal, Arash Vahdat, Jan Kautz:
PhysDiff: Physics-Guided Human Motion Diffusion Model. ICCV 2023: 15964-15975 - [c48]Jiaming Song, Arash Vahdat, Morteza Mardani, Jan Kautz:
Pseudoinverse-Guided Diffusion Models for Inverse Problems. ICLR 2023 - [c47]Guan-Horng Liu, Arash Vahdat, De-An Huang, Evangelos A. Theodorou, Weili Nie, Anima Anandkumar:
I2SB: Image-to-Image Schrödinger Bridge. ICML 2023: 22042-22062 - [c46]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: 32483-32498 - [c45]Hongkai Zheng, Weili Nie, Arash Vahdat, Kamyar Azizzadenesheli, Anima Anandkumar:
Fast Sampling of Diffusion Models via Operator Learning. ICML 2023: 42390-42402 - [d1]Zhuoran Qiao, Weili Nie, Arash Vahdat, Thomas F. Miller III, Animashree Anandkumar:
NeuralPLexer evaluation datasets and predictions. Zenodo, 2023
- [i44]Guan-Horng Liu, Arash Vahdat, De-An Huang, Evangelos A. Theodorou, Weili Nie, Anima Anandkumar:
I2SB: Image-to-Image Schrödinger Bridge. CoRR abs/2302.05872 (2023) - [i43]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 abs/2302.07400 (2023) - [i42]Jiarui Xu, Sifei Liu, Arash Vahdat, Wonmin Byeon, Xiaolong Wang, Shalini De Mello:
Open-Vocabulary Panoptic Segmentation with Text-to-Image Diffusion Models. CoRR abs/2303.04803 (2023) - [i41]Paul Micaelli, Arash Vahdat, Hongxu Yin, Jan Kautz, Pavlo Molchanov:
Recurrence without Recurrence: Stable Video Landmark Detection with Deep Equilibrium Models. CoRR abs/2304.00600 (2023) - [i40]Morteza Mardani, Jiaming Song, Jan Kautz, Arash Vahdat:
A Variational Perspective on Solving Inverse Problems with Diffusion Models. CoRR abs/2305.04391 (2023) - [i39]Hongkai Zheng, Weili Nie, Arash Vahdat, Anima Anandkumar:
Fast Training of Diffusion Models with Masked Transformers. CoRR abs/2306.09305 (2023) - [i38]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 abs/2309.15214 (2023) - [i37]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 abs/2310.04610 (2023) - [i36]Ali Hatamizadeh, Jiaming Song, Guilin Liu, Jan Kautz, Arash Vahdat:
DiffiT: Diffusion Vision Transformers for Image Generation. CoRR abs/2312.02139 (2023) - 2022
- [c44]Sina Mohseni, Arash Vahdat, Jay Yadawa:
Shifting Transformation Learning for Robust Out-of-Distribution Detection. BMVC 2022: 679 - [c43]Hongxu Yin, Arash Vahdat, José M. Álvarez, Arun Mallya, Jan Kautz, Pavlo Molchanov:
A-ViT: Adaptive Tokens for Efficient Vision Transformer. CVPR 2022: 10799-10808 - [c42]Pavlo Molchanov, Jimmy Hall, Hongxu Yin, Jan Kautz, Nicolò Fusi, Arash Vahdat:
LANA: Latency Aware Network Acceleration. ECCV (12) 2022: 137-156 - [c41]Tim Dockhorn, Arash Vahdat, Karsten Kreis:
Score-Based Generative Modeling with Critically-Damped Langevin Diffusion. ICLR 2022 - [c40]Zhisheng Xiao, Karsten Kreis, Arash Vahdat:
Tackling the Generative Learning Trilemma with Denoising Diffusion GANs. ICLR 2022 - [c39]Weili Nie, Brandon Guo, Yujia Huang, Chaowei Xiao, Arash Vahdat, Animashree Anandkumar:
Diffusion Models for Adversarial Purification. ICML 2022: 16805-16827 - [c38]Tim Dockhorn, Arash Vahdat, Karsten Kreis:
GENIE: Higher-Order Denoising Diffusion Solvers. NeurIPS 2022 - [c37]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 - [i35]Weili Nie, Brandon Guo, Yujia Huang, Chaowei Xiao, Arash Vahdat, Anima Anandkumar:
Diffusion Models for Adversarial Purification. CoRR abs/2205.07460 (2022) - [i34]Zhuoran Qiao, Weili Nie, Arash Vahdat, Thomas F. Miller III, Anima Anandkumar:
Dynamic-Backbone Protein-Ligand Structure Prediction with Multiscale Generative Diffusion Models. CoRR abs/2209.15171 (2022) - [i33]Tim Dockhorn, Arash Vahdat, Karsten Kreis:
GENIE: Higher-Order Denoising Diffusion Solvers. CoRR abs/2210.05475 (2022) - [i32]Xiaohui Zeng, Arash Vahdat, Francis Williams, Zan Gojcic, Or Litany, Sanja Fidler, Karsten Kreis:
LION: Latent Point Diffusion Models for 3D Shape Generation. CoRR abs/2210.06978 (2022) - [i31]Tim Dockhorn, Tianshi Cao, Arash Vahdat, Karsten Kreis:
Differentially Private Diffusion Models. CoRR abs/2210.09929 (2022) - [i30]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 abs/2211.01324 (2022) - [i29]Hongkai Zheng, Weili Nie, Arash Vahdat, Kamyar Azizzadenesheli, Anima Anandkumar:
Fast Sampling of Diffusion Models via Operator Learning. CoRR abs/2211.13449 (2022) - [i28]Ye Yuan, Jiaming Song, Umar Iqbal, Arash Vahdat, Jan Kautz:
PhysDiff: Physics-Guided Human Motion Diffusion Model. CoRR abs/2212.02500 (2022) - 2021
- [c36]Hongxu Yin, Arun Mallya, Arash Vahdat, José M. Álvarez, Jan Kautz, Pavlo Molchanov:
See Through Gradients: Image Batch Recovery via GradInversion. CVPR 2021: 16337-16346 - [c35]Zhisheng Xiao, Karsten Kreis, Jan Kautz, Arash Vahdat:
VAEBM: A Symbiosis between Variational Autoencoders and Energy-based Models. ICLR 2021 - [c34]Jyoti Aneja, Alexander G. Schwing, Jan Kautz, Arash Vahdat:
A Contrastive Learning Approach for Training Variational Autoencoder Priors. NeurIPS 2021: 480-493 - [c33]Arash Vahdat, Karsten Kreis, Jan Kautz:
Score-based Generative Modeling in Latent Space. NeurIPS 2021: 11287-11302 - [c32]Tianshi Cao, Alex Bie, Arash Vahdat, Sanja Fidler, Karsten Kreis:
Don't Generate Me: Training Differentially Private Generative Models with Sinkhorn Divergence. NeurIPS 2021: 12480-12492 - [c31]Weili Nie, Arash Vahdat, Anima Anandkumar:
Controllable and Compositional Generation with Latent-Space Energy-Based Models. NeurIPS 2021: 13497-13510 - [i27]Hongxu Yin, Arun Mallya, Arash Vahdat, José M. Álvarez, Jan Kautz, Pavlo Molchanov:
See through Gradients: Image Batch Recovery via GradInversion. CoRR abs/2104.07586 (2021) - [i26]Sina Mohseni, Arash Vahdat, Jay Yadawa:
Multi-task Transformation Learning for Robust Out-of-Distribution Detection. CoRR abs/2106.03899 (2021) - [i25]Arash Vahdat, Karsten Kreis, Jan Kautz:
Score-based Generative Modeling in Latent Space. CoRR abs/2106.05931 (2021) - [i24]Pavlo Molchanov, Jimmy Hall, Hongxu Yin, Jan Kautz, Nicolò Fusi, Arash Vahdat:
HANT: Hardware-Aware Network Transformation. CoRR abs/2107.10624 (2021) - [i23]Weili Nie, Arash Vahdat, Anima Anandkumar:
Controllable and Compositional Generation with Latent-Space Energy-Based Models. CoRR abs/2110.10873 (2021) - [i22]Tianshi Cao, Alex Bie, Arash Vahdat, Sanja Fidler, Karsten Kreis:
Don't Generate Me: Training Differentially Private Generative Models with Sinkhorn Divergence. CoRR abs/2111.01177 (2021) - [i21]Tim Dockhorn, Arash Vahdat, Karsten Kreis:
Score-Based Generative Modeling with Critically-Damped Langevin Diffusion. CoRR abs/2112.07068 (2021) - [i20]Hongxu Yin, Arash Vahdat, José M. Álvarez, Arun Mallya, Jan Kautz, Pavlo Molchanov:
AdaViT: Adaptive Tokens for Efficient Vision Transformer. CoRR abs/2112.07658 (2021) - [i19]Zhisheng Xiao, Karsten Kreis, Arash Vahdat:
Tackling the Generative Learning Trilemma with Denoising Diffusion GANs. CoRR abs/2112.07804 (2021) - 2020
- [c30]Arash Vahdat, Arun Mallya, Ming-Yu Liu, Jan Kautz:
UNAS: Differentiable Architecture Search Meets Reinforcement Learning. CVPR 2020: 11263-11272 - [c29]Mostafa S. Ibrahim, Arash Vahdat, Mani Ranjbar, William G. Macready:
Semi-Supervised Semantic Image Segmentation With Self-Correcting Networks. CVPR 2020: 12712-12722 - [c28]Tanmay Gupta, Arash Vahdat, Gal Chechik, Xiaodong Yang, Jan Kautz, Derek Hoiem:
Contrastive Learning for Weakly Supervised Phrase Grounding. ECCV (3) 2020: 752-768 - [c27]Arash Vahdat, Evgeny Andriyash, William G. Macready:
Undirected Graphical Models as Approximate Posteriors. ICML 2020: 9680-9689 - [c26]Jeremy Bernstein, Arash Vahdat, Yisong Yue, Ming-Yu Liu:
On the distance between two neural networks and the stability of learning. NeurIPS 2020 - [c25]Arash Vahdat, Jan Kautz:
NVAE: A Deep Hierarchical Variational Autoencoder. NeurIPS 2020 - [i18]Jeremy Bernstein, Arash Vahdat, Yisong Yue, Ming-Yu Liu:
On the distance between two neural networks and the stability of learning. CoRR abs/2002.03432 (2020) - [i17]Tanmay Gupta, Arash Vahdat, Gal Chechik, Xiaodong Yang, Jan Kautz, Derek Hoiem:
Contrastive Learning for Weakly Supervised Phrase Grounding. CoRR abs/2006.09920 (2020) - [i16]Arash Vahdat, Jan Kautz:
NVAE: A Deep Hierarchical Variational Autoencoder. CoRR abs/2007.03898 (2020) - [i15]Zhisheng Xiao, Karsten Kreis, Jan Kautz, Arash Vahdat:
VAEBM: A Symbiosis between Variational Autoencoders and Energy-based Models. CoRR abs/2010.00654 (2020) - [i14]Jyoti Aneja, Alexander G. Schwing, Jan Kautz, Arash Vahdat:
NCP-VAE: Variational Autoencoders with Noise Contrastive Priors. CoRR abs/2010.02917 (2020)
2010 – 2019
- 2019
- [c24]Mehran Khodabandeh, Arash Vahdat, Mani Ranjbar, William G. Macready:
A Robust Learning Approach to Domain Adaptive Object Detection. ICCV 2019: 480-490 - [i13]Arash Vahdat, Evgeny Andriyash, William G. Macready:
Learning Undirected Posteriors by Backpropagation through MCMC Updates. CoRR abs/1901.03440 (2019) - [i12]Mehran Khodabandeh, Arash Vahdat, Mani Ranjbar, William G. Macready:
A Robust Learning Approach to Domain Adaptive Object Detection. CoRR abs/1904.02361 (2019) - [i11]Arash Vahdat, Arun Mallya, Ming-Yu Liu, Jan Kautz:
UNAS: Differentiable Architecture Search Meets Reinforcement Learning. CoRR abs/1912.07651 (2019) - 2018
- [c23]Arash Vahdat, William G. Macready, Zhengbing Bian, Amir Khoshaman, Evgeny Andriyash:
DVAE++: Discrete Variational Autoencoders with Overlapping Transformations. ICML 2018: 5042-5051 - [c22]Arash Vahdat, Evgeny Andriyash, William G. Macready:
DVAE#: Discrete Variational Autoencoders with Relaxed Boltzmann Priors. NeurIPS 2018: 1869-1878 - [i10]Arash Vahdat, William G. Macready, Zhengbing Bian, Amir Khoshaman:
DVAE++: Discrete Variational Autoencoders with Overlapping Transformations. CoRR abs/1802.04920 (2018) - [i9]Arash Vahdat, Evgeny Andriyash, William G. Macready:
DVAE#: Discrete Variational Autoencoders with Relaxed Boltzmann Priors. CoRR abs/1805.07445 (2018) - [i8]Evgeny Andriyash, Arash Vahdat, William G. Macready:
Improved Gradient-Based Optimization Over Discrete Distributions. CoRR abs/1810.00116 (2018) - [i7]Mostafa S. Ibrahim, Arash Vahdat, William G. Macready:
Weakly Supervised Semantic Image Segmentation with Self-correcting Networks. CoRR abs/1811.07073 (2018) - 2017
- [c21]Arash Vahdat:
Toward Robustness against Label Noise in Training Deep Discriminative Neural Networks. NIPS 2017: 5596-5605 - [i6]Arash Vahdat:
Toward Robustness against Label Noise in Training Deep Discriminative Neural Networks. CoRR abs/1706.00038 (2017) - 2016
- [c20]Mostafa S. Ibrahim, Srikanth Muralidharan, Zhiwei Deng, Arash Vahdat, Greg Mori:
A Hierarchical Deep Temporal Model for Group Activity Recognition. CVPR 2016: 1971-1980 - [c19]Zhiwei Deng, Arash Vahdat, Hexiang Hu, Greg Mori:
Structure Inference Machines: Recurrent Neural Networks for Analyzing Relations in Group Activity Recognition. CVPR 2016: 4772-4781 - [c18]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: 2392-2397 - [i5]Mostafa S. Ibrahim, Srikanth Muralidharan, Zhiwei Deng, Arash Vahdat, Greg Mori:
Hierarchical Deep Temporal Models for Group Activity Recognition. CoRR abs/1607.02643 (2016) - 2015
- [j2]Yasaman S. Sefidgar, Arash Vahdat, Stephen Se, Greg Mori:
Discriminative key-component models for interaction detection and recognition. Comput. Vis. Image Underst. 135: 16-30 (2015) - [c17]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: 9-18 - [c16]Hossein Hajimirsadeghi, Wang Yan, Arash Vahdat, Greg Mori:
Visual recognition by counting instances: A multi-instance cardinality potential kernel. CVPR 2015: 2596-2605 - [i4]Hossein Hajimirsadeghi, Wang Yan, Arash Vahdat, Greg Mori:
Visual Recognition by Counting Instances: A Multi-Instance Cardinality Potential Kernel. CoRR abs/1502.02063 (2015) - [i3]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 abs/1502.03851 (2015) - [i2]Zhiwei Deng, Arash Vahdat, Hexiang Hu, Greg Mori:
Structure Inference Machines: Recurrent Neural Networks for Analyzing Relations in Group Activity Recognition. CoRR abs/1511.04196 (2015) - [i1]Mostafa S. Ibrahim, Srikanth Muralidharan, Zhiwei Deng, Arash Vahdat, Greg Mori:
A Hierarchical Deep Temporal Model for Group Activity Recognition. CoRR abs/1511.06040 (2015) - 2014
- [j1]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): 49-69 (2014) - [c15]Arash Vahdat, Guang-Tong Zhou, Greg Mori:
Discovering Video Clusters from Visual Features and Noisy Tags. ECCV (6) 2014: 526-539 - 2013
- [c14]Arash Vahdat, Greg Mori:
Handling Uncertain Tags in Visual Recognition. ICCV 2013: 737-744 - [c13]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: 1185-1192 - [c12]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: 637-640 - [c11]Guang-Tong Zhou, Tian Lan, Arash Vahdat, Greg Mori:
Latent Maximum Margin Clustering. NIPS 2013: 28-36 - [c10]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 - 2012
- [c9]Mani Ranjbar, Arash Vahdat, Greg Mori:
Complex loss optimization via dual decomposition. CVPR 2012: 2304-2311 - [c8]Nataliya Shapovalova, Arash Vahdat, Kevin J. Cannons, Tian Lan, Greg Mori:
Similarity Constrained Latent Support Vector Machine: An Application to Weakly Supervised Action Classification. ECCV (7) 2012: 55-68 - [c7]Weilong Yang, Yang Wang, Arash Vahdat, Greg Mori:
Kernel Latent SVM for Visual Recognition. NIPS 2012: 818-826 - [c6]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:
TRECVID 2012 GENIE: Multimedia Event Detection and Recounting. TRECVID 2012 - 2011
- [c5]Arash Vahdat, Bo Gao, Mani Ranjbar, Greg Mori:
A discriminative key pose sequence model for recognizing human interactions. ICCV Workshops 2011: 1729-1736 - [c4]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:
GENIE TRECVID 2011 Multimedia Event Detection: Late-Fusion Approaches to Combine Multiple Audio-Visual features. TRECVID 2011 - 2010
- [c3]Arash Vahdat, Mark S. Drew:
Colour From Grey by Optimized Colour Ordering. CIC 2010: 17-21 - [c2]Bernard Ng, Arash Vahdat, Ghassan Hamarneh, Rafeef Abugharbieh:
Generalized Sparse Classifiers for Decoding Cognitive States in fMRI. MLMI 2010: 108-115
2000 – 2009
- 2009
- [c1]Mohammad H. Rohban, Hamid R. Rabiee, Arash Vahdat:
Face virtual pose generation using aligned locally linear regression for face recognition. ICIP 2009: 4121-4124
Coauthor Index
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Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-10-14 23:26 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
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since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
