Face virtual pose generation using aligned locally linear regression for face recognition. - Mohammad H. Rohban; Hamid R. Rabiee; Arash Vahdat (ICIP, 2009)

Colour From Grey by Optimized Colour Ordering. - Arash Vahdat; Mark S. Drew (CIC, 2010)

Generalized Sparse Classifiers for Decoding Cognitive States in fMRI. - Bernard Ng; Arash Vahdat; Ghassan Hamarneh; Rafeef Abugharbieh (MLMI, 2010)

A discriminative key pose sequence model for recognizing human interactions. - Arash Vahdat; Bo Gao; Mani Ranjbar; Greg Mori (ICCV Workshops, 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 001; Scott McCloskey; Jingchen Liu; Ben Miller; Zhi Feng Huang; Arash Vahdat; Weilong Yang; et al. (TRECVID, 2011)

Complex loss optimization via dual decomposition. - Mani Ranjbar; Arash Vahdat; Greg Mori (CVPR, 2012)

Similarity Constrained Latent Support Vector Machine: An Application to Weakly Supervised Action Classification. - Nataliya Shapovalova; Arash Vahdat; Kevin J. Cannons; Tian Lan 006; Greg Mori (ECCV (7), 2012)

Kernel Latent SVM for Visual Recognition. - Weilong Yang; Yang Wang 003; Arash Vahdat; Greg Mori (NIPS, 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; et al. (TRECVID, 2012)

Compositional Models for Video Event Detection: A Multiple Kernel Learning Latent Variable Approach. - Arash Vahdat; Kevin J. Cannons; Greg Mori; Sangmin Oh; Ilseo Kim (ICCV, 2013)

Handling Uncertain Tags in Visual Recognition. - Arash Vahdat; Greg Mori (ICCV, 2013)

Segmental multi-way local pooling for video recognition. - Ilseo Kim; Sangmin Oh; Arash Vahdat; Kevin J. Cannons; A. G. Amitha Perera; Greg Mori (ACM Multimedia, 2013)

Latent Maximum Margin Clustering. - Guang-Tong Zhou; Tian Lan 006; Arash Vahdat; Greg Mori (NIPS, 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 001; et al. (TRECVID, 2013)

Discovering Video Clusters from Visual Features and Noisy Tags. - Arash Vahdat; Guang-Tong Zhou; Greg Mori (ECCV (6), 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)

Visual recognition by counting instances: A multi-instance cardinality potential kernel. - Hossein Hajimirsadeghi; Wang Yan; Arash Vahdat; Greg Mori (CVPR, 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 (CVPR Workshops, 2015)

Discriminative key-component models for interaction detection and recognition. - Yasaman S. Sefidgar; Arash Vahdat; Stephen Se; Greg Mori (Comput. Vis. Image Underst., 2015)

Structure Inference Machines: Recurrent Neural Networks for Analyzing Relations in Group Activity Recognition. - Zhiwei Deng; Arash Vahdat; Hexiang Hu; Greg Mori (CVPR, 2016)

A Hierarchical Deep Temporal Model for Group Activity Recognition. - Mostafa S. Ibrahim; Srikanth Muralidharan; Zhiwei Deng; Arash Vahdat; Greg Mori (CVPR, 2016)

Unsupervised learning of supervoxel embeddings for video Segmentation. - Mehran Khodabandeh; Srikanth Muralidharan; Arash Vahdat; Nazanin Mehrasa; Eduardo M. Pereira; Shin'ichi Satoh 001; Greg Mori (ICPR, 2016)

Hierarchical Deep Temporal Models for Group Activity Recognition. - Mostafa S. Ibrahim; Srikanth Muralidharan; Zhiwei Deng; Arash Vahdat; Greg Mori (CoRR, 2016)

Toward Robustness against Label Noise in Training Deep Discriminative Neural Networks. - Arash Vahdat (NIPS, 2017)

DVAE++: Discrete Variational Autoencoders with Overlapping Transformations. - Arash Vahdat; William G. Macready; Zhengbing Bian; Amir Khoshaman; Evgeny Andriyash (ICML, 2018)

DVAE#: Discrete Variational Autoencoders with Relaxed Boltzmann Priors. - Arash Vahdat; Evgeny Andriyash; William G. Macready (NeurIPS, 2018)

DVAE++: Discrete Variational Autoencoders with Overlapping Transformations. - Arash Vahdat; William G. Macready; Zhengbing Bian; Amir Khoshaman (CoRR, 2018)

Improved Gradient-Based Optimization Over Discrete Distributions. - Evgeny Andriyash; Arash Vahdat; William G. Macready (CoRR, 2018)

Weakly Supervised Semantic Image Segmentation with Self-correcting Networks. - Mostafa S. Ibrahim; Arash Vahdat; William G. Macready (CoRR, 2018)

A Robust Learning Approach to Domain Adaptive Object Detection. - Mehran Khodabandeh; Arash Vahdat; Mani Ranjbar; William G. Macready (ICCV, 2019)

Learning Undirected Posteriors by Backpropagation through MCMC Updates. - Arash Vahdat; Evgeny Andriyash; William G. Macready (CoRR, 2019)

Semi-Supervised Semantic Image Segmentation With Self-Correcting Networks. - Mostafa S. Ibrahim; Arash Vahdat; Mani Ranjbar; William G. Macready (CVPR, 2020)

UNAS: Differentiable Architecture Search Meets Reinforcement Learning. - Arash Vahdat; Arun Mallya; Ming-Yu Liu 001; Jan Kautz (CVPR, 2020)

Contrastive Learning for Weakly Supervised Phrase Grounding. - Tanmay Gupta; Arash Vahdat; Gal Chechik; Xiaodong Yang 001; Jan Kautz; Derek Hoiem (ECCV (3), 2020)

Undirected Graphical Models as Approximate Posteriors. - Arash Vahdat; Evgeny Andriyash; William G. Macready (ICML, 2020)

On the distance between two neural networks and the stability of learning. - Jeremy Bernstein; Arash Vahdat; Yisong Yue; Ming-Yu Liu 001 (NeurIPS, 2020)

NVAE: A Deep Hierarchical Variational Autoencoder. - Arash Vahdat; Jan Kautz (NeurIPS, 2020)

NCP-VAE: Variational Autoencoders with Noise Contrastive Priors. - Jyoti Aneja; Alexander G. Schwing; Jan Kautz; Arash Vahdat (CoRR, 2020)

See Through Gradients: Image Batch Recovery via GradInversion. - Hongxu Yin; Arun Mallya; Arash Vahdat; José M. Álvarez 004; Jan Kautz; Pavlo Molchanov 001 (CVPR, 2021)

VAEBM: A Symbiosis between Variational Autoencoders and Energy-based Models. - Zhisheng Xiao; Karsten Kreis; Jan Kautz; Arash Vahdat (ICLR, 2021)

A Contrastive Learning Approach for Training Variational Autoencoder Priors. - Jyoti Aneja; Alexander G. Schwing; Jan Kautz; Arash Vahdat (NeurIPS, 2021)

Don't Generate Me: Training Differentially Private Generative Models with Sinkhorn Divergence. - Tianshi Cao; Alex Bie; Arash Vahdat; Sanja Fidler; Karsten Kreis (NeurIPS, 2021)

Controllable and Compositional Generation with Latent-Space Energy-Based Models. - Weili Nie; Arash Vahdat; Anima Anandkumar (NeurIPS, 2021)

Score-based Generative Modeling in Latent Space. - Arash Vahdat; Karsten Kreis; Jan Kautz (NeurIPS, 2021)

Multi-task Transformation Learning for Robust Out-of-Distribution Detection. - Sina Mohseni; Arash Vahdat; Jay Yadawa (CoRR, 2021)

HANT: Hardware-Aware Network Transformation. - Pavlo Molchanov 001; Jimmy Hall; Hongxu Yin; Jan Kautz; Nicolò Fusi; Arash Vahdat (CoRR, 2021)

AdaViT: Adaptive Tokens for Efficient Vision Transformer. - Hongxu Yin; Arash Vahdat; José M. Álvarez 004; Arun Mallya; Jan Kautz; Pavlo Molchanov 001 (CoRR, 2021)

Shifting Transformation Learning for Robust Out-of-Distribution Detection. - Sina Mohseni; Arash Vahdat; Jay Yadawa (BMVC, 2022)

A-ViT: Adaptive Tokens for Efficient Vision Transformer. - Hongxu Yin; Arash Vahdat; José M. Álvarez 004; Arun Mallya; Jan Kautz; Pavlo Molchanov 001 (CVPR, 2022)

LANA: Latency Aware Network Acceleration. - Pavlo Molchanov 001; Jimmy Hall; Hongxu Yin; Jan Kautz; Nicolò Fusi; Arash Vahdat (ECCV (12), 2022)

Score-Based Generative Modeling with Critically-Damped Langevin Diffusion. - Tim Dockhorn; Arash Vahdat; Karsten Kreis (ICLR, 2022)

Tackling the Generative Learning Trilemma with Denoising Diffusion GANs. - Zhisheng Xiao; Karsten Kreis; Arash Vahdat (ICLR, 2022)

Diffusion Models for Adversarial Purification. - Weili Nie; Brandon Guo; Yujia Huang; Chaowei Xiao; Arash Vahdat; Animashree Anandkumar (ICML, 2022)

GENIE: Higher-Order Denoising Diffusion Solvers. - Tim Dockhorn; Arash Vahdat; Karsten Kreis (NeurIPS, 2022)

LION: Latent Point Diffusion Models for 3D Shape Generation. - Xiaohui Zeng; Arash Vahdat; Francis Williams; Zan Gojcic; Or Litany; Sanja Fidler; Karsten Kreis (NeurIPS, 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)

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 001 (CoRR, 2022)

Recurrence without Recurrence: Stable Video Landmark Detection with Deep Equilibrium Models. - Paul Micaelli; Arash Vahdat; Hongxu Yin; Jan Kautz; Pavlo Molchanov 001 (CVPR, 2023)

Open-Vocabulary Panoptic Segmentation with Text-to-Image Diffusion Models. - Jiarui Xu; Sifei Liu; Arash Vahdat; Wonmin Byeon; Xiaolong Wang 004; Shalini De Mello (CVPR, 2023)

PhysDiff: Physics-Guided Human Motion Diffusion Model. - Ye Yuan 007; Jiaming Song; Umar Iqbal 001; Arash Vahdat; Jan Kautz (ICCV, 2023)

Pseudoinverse-Guided Diffusion Models for Inverse Problems. - Jiaming Song; Arash Vahdat; Morteza Mardani; Jan Kautz (ICLR, 2023)

I2SB: Image-to-Image Schrödinger Bridge. - Guan-Horng Liu; Arash Vahdat; De-An Huang; Evangelos A. Theodorou; Weili Nie; Anima Anandkumar (ICML, 2023)

Loss-Guided Diffusion Models for Plug-and-Play Controllable Generation. - Jiaming Song; Qinsheng Zhang; Hongxu Yin; Morteza Mardani; Ming-Yu Liu 001; Jan Kautz; Yongxin Chen; Arash Vahdat (ICML, 2023)

Fast Sampling of Diffusion Models via Operator Learning. - Hongkai Zheng; Weili Nie; Arash Vahdat; Kamyar Azizzadenesheli; Anima Anandkumar (ICML, 2023)

Score-based Diffusion Models in Function Space. - Jae Hyun Lim 001; Nikola B. Kovachki; Ricardo Baptista; Christopher Beckham; Kamyar Azizzadenesheli; Jean Kossaifi; Vikram Voleti; Jiaming Song; Karsten Kreis; Jan Kautz; Christopher Pal; Arash Vahdat; et al. (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)

DeepSpeed4Science Initiative: Enabling Large-Scale Scientific Discovery through Sophisticated AI System Technologies. - Shuaiwen Leon Song; Bonnie Kruft; Minjia Zhang; Conglong Li; Shiyang Chen 004; Chengming Zhang 006; Masahiro Tanaka; Xiaoxia Wu; Jeff Rasley; Ammar Ahmad Awan; Connor Holmes; Martin Cai; et al. (CoRR, 2023)

Differentially Private Diffusion Models. - Tim Dockhorn; Tianshi Cao; Arash Vahdat; Karsten Kreis (Trans. Mach. Learn. Res., 2023)

Dr-Fairness: Dynamic Data Ratio Adjustment for Fair Training on Real and Generated Data. - Yuji Roh; Weili Nie; De-An Huang; Steven Euijong Whang; Arash Vahdat; Anima Anandkumar (Trans. Mach. Learn. Res., 2023)

NeuralPLexer evaluation datasets and predictions. - Zhuoran Qiao; Weili Nie; Arash Vahdat; Thomas F. Miller III; Animashree Anandkumar (Zenodo, 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; et al. (Int. J. High Perform. Comput. Appl., 2023)

NeuralPLexer evaluation datasets and predictions. - Zhuoran Qiao; Weili Nie; Arash Vahdat; Thomas F. Miller III; Animashree Anandkumar (Zenodo, 2023)

DiffiT: Diffusion Vision Transformers for Image Generation. - Ali Hatamizadeh; Jiaming Song; Guilin Liu; Jan Kautz; Arash Vahdat (ECCV (8), 2024)

Compositional Text-to-Image Generation with Feedforward Layout Generation. - Sifei Liu; Weili Nie; An-Chieh Cheng; Morteza Mardani; Chao Liu 064; Benjamin Eckart; Arash Vahdat (ECCV Workshops (11), 2024)

A Variational Perspective on Solving Inverse Problems with Diffusion Models. - Morteza Mardani; Jiaming Song; Jan Kautz; Arash Vahdat (ICLR, 2024)

Compositional Text-to-Image Generation with Dense Blob Representations. - Weili Nie; Sifei Liu; Morteza Mardani; Chao Liu 064; Benjamin Eckart; Arash Vahdat (ICML, 2024)

DisCo-Diff: Enhancing Continuous Diffusion Models with Discrete Latents. - Yilun Xu; Gabriele Corso; Tommi S. Jaakkola; Arash Vahdat; Karsten Kreis (ICML, 2024)

Warped Diffusion: Solving Video Inverse Problems with Image Diffusion Models. - Giannis Daras; Weili Nie; Karsten Kreis; Alex Dimakis; Morteza Mardani; Nikola B. Kovachki; Arash Vahdat (NeurIPS, 2024)

Aligning Target-Aware Molecule Diffusion Models with Exact Energy Optimization. - Siyi Gu; Minkai Xu; Alexander S. Powers; Weili Nie; Tomas Geffner; Karsten Kreis; Jure Leskovec; Arash Vahdat; Stefano Ermon (NeurIPS, 2024)

Molecule Generation with Fragment Retrieval Augmentation. - Seul Lee; Karsten Kreis; Srimukh Prasad Veccham; Meng Liu 015; Danny Reidenbach; Saee Paliwal; Arash Vahdat; Weili Nie (NeurIPS, 2024)

BlobGEN-3D: Compositional 3D-Consistent Freeview Image Generation with 3D Blobs. - Chao Liu 064; Weili Nie; Sifei Liu; Abhishek Badki; Hang Su 005; Morteza Mardani; Benjamin Eckart; Arash Vahdat (SIGGRAPH Asia, 2024)

DiffUHaul: A Training-Free Method for Object Dragging in Images. - Omri Avrahami; Rinon Gal; Gal Chechik; Ohad Fried; Dani Lischinski; Arash Vahdat; Weili Nie (SIGGRAPH Asia, 2024)

CamCo: Camera-Controllable 3D-Consistent Image-to-Video Generation. - Dejia Xu; Weili Nie; Chao Liu 064; Sifei Liu; Jan Kautz; Zhangyang Wang; Arash Vahdat (CoRR, 2024)

Kilometer-Scale Convection Allowing Model Emulation using Generative Diffusion Modeling. - 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 (CoRR, 2024)

Stochastic Flow Matching for Resolving Small-Scale Physics. - Stathi Fotiadis; Noah D. Brenowitz; Tomas Geffner; Yair Cohen; Michael S. Pritchard; Arash Vahdat; Morteza Mardani (CoRR, 2024)

State-specific protein-ligand complex structure prediction with a multiscale deep generative model. - Zhuoran Qiao; Weili Nie; Arash Vahdat; Thomas F. Miller III; Animashree Anandkumar (Nat. Mac. Intell., 2024)

AGG: Amortized Generative 3D Gaussians for Single Image to 3D. - Dejia Xu; Ye Yuan 012; Morteza Mardani; Sifei Liu; Jiaming Song; Zhangyang Wang; Arash Vahdat (Trans. Mach. Learn. Res., 2024)

Fast Training of Diffusion Models with Masked Transformers. - Hongkai Zheng; Weili Nie; Arash Vahdat; Anima Anandkumar (Trans. Mach. Learn. Res., 2024)

BlobGEN-Vid: Compositional Text-to-Video Generation with Blob Video Representations. - Weixi Feng; Chao Liu 064; Sifei Liu; William Yang Wang; Arash Vahdat; Weili Nie (CVPR, 2025)

Proteina: Scaling Flow-based Protein Structure Generative Models. - Tomas Geffner; Kieran Didi; Zuobai Zhang; Danny Reidenbach; Zhonglin Cao; Jason Yim; Mario Geiger; Christian Dallago; Emine Küçükbenli; Arash Vahdat; Karsten Kreis (ICLR, 2025)

Not-So-Optimal Transport Flows for 3D Point Cloud Generation. - Ka-Hei Hui; Chao Liu; Xiaohui Zeng; Chi-Wing Fu; Arash Vahdat (ICLR, 2025)

Truncated Consistency Models. - Sangyun Lee; Yilun Xu; Tomas Geffner; Giulia Fanti; Karsten Kreis; Arash Vahdat; Weili Nie (ICLR, 2025)

Heavy-Tailed Diffusion Models. - Kushagra Pandey; Jaideep Pathak; Yilun Xu; Stephan Mandt; Michael S. Pritchard; Arash Vahdat; Morteza Mardani (ICLR, 2025)

ProtComposer: Compositional Protein Structure Generation with 3D Ellipsoids. - Hannes Stärk; Bowen Jing; Tomas Geffner; Jason Yim; Tommi S. Jaakkola; Arash Vahdat; Karsten Kreis (ICLR, 2025)

Energy-Based Diffusion Language Models for Text Generation. - Minkai Xu; Tomas Geffner; Karsten Kreis; Weili Nie; Yilun Xu; Jure Leskovec; Stefano Ermon; Arash Vahdat (ICLR, 2025)

Elucidating Optimal Reward-Diversity Tradeoffs in Text-to-Image Diffusion Models. - Rohit Jena; Ali Taghibakhshi; Sahil Jain; Gerald Shen; Nima Tajbakhsh; Arash Vahdat (WACV, 2025)

GenMol: A Drug Discovery Generalist with Discrete Diffusion. - Seul Lee; Karsten Kreis; Srimukh Prasad Veccham; Meng Liu 015; Danny Reidenbach; Yuxing Peng 005; Saee Paliwal; Weili Nie; Arash Vahdat (CoRR, 2025)

A2SB: Audio-to-Audio Schrodinger Bridges. - Zhifeng Kong; Kevin J. Shih; Weili Nie; Arash Vahdat; Sang-gil Lee; João Felipe Santos; Ante Jukic; Rafael Valle; Bryan Catanzaro (CoRR, 2025)

One-step Diffusion Models with f-Divergence Distribution Matching. - Yilun Xu; Weili Nie; Arash Vahdat (CoRR, 2025)

EquiVDM: Equivariant Video Diffusion Models with Temporally Consistent Noise. - Chao Liu 064; Arash Vahdat (CoRR, 2025)

Esoteric Language Models. - Subham Sekhar Sahoo; Zhihan Yang; Yash Akhauri; Johnna Liu; Deepansha Singh; Zhoujun Cheng; Zhengzhong Liu 001; Eric Xing; John Thickstun; Arash Vahdat (CoRR, 2025)

Elucidated Rolling Diffusion Models for Probabilistic Weather Forecasting. - Salva Rühling Cachay; Miika Aittala; Karsten Kreis; Noah D. Brenowitz; Arash Vahdat; Morteza Mardani; Rose Yu (CoRR, 2025)

La-Proteina: Atomistic Protein Generation via Partially Latent Flow Matching. - Tomas Geffner; Kieran Didi; Zhonglin Cao; Danny Reidenbach; Zuobai Zhang; Christian Dallago; Emine Küçükbenli; Karsten Kreis; Arash Vahdat (CoRR, 2025)

Trust Region Constrained Measure Transport in Path Space for Stochastic Optimal Control and Inference. - Denis Blessing; Julius Berner; Lorenz Richter; Carles Domingo-Enrich; Yuanqi Du; Arash Vahdat; Gerhard Neumann (CoRR, 2025)