Publications | Fundamental Generative AI Research

Amirmojtaba Sabour, Michael Samuel Albergo, Carles Domingo-Enrich, Nicholas Matthew Boffi, Sanja Fidler, Karsten Kreis, Eric Vanden-Eijnden (2026). Test-time Scaling of Diffusions with Flow Maps. Advances in Neural Information Processing Systems (NeurIPS).

arXiv

Jean-Marie Lemercier, Tomas Geffner, Morteza Mardani, Karsten Kreis, Arash Vahdat, Ante Jukić (2026). DiLaDiff: Distilled Latent-augmented Diffusion for Language Modeling. Advances in Neural Information Processing Systems (NeurIPS).

arXiv

Abbas Mammadov, So Takao, Bohan Chen, Ricardo Baptista, Morteza Mardani, Yee Whye Teh, Julius Berner (2026). Variational Flow Maps: Make Some Noise for One-Step Conditional Generation. International Conference on Machine Learning (ICML).

arXiv

Shengqu Cai, Weili Nie, Chao Liu, Julius Berner, Lvmin Zhang, Nanye Ma, Hansheng Chen, Maneesh Agrawala, Leonidas Guibas, Gordon Wetzstein, Arash Vahdat (2026). Mode Seeking meets Mean Seeking for Fast Long Video Generation. International Conference on Machine Learning (ICML).

arXiv

Xinyin Ma, Julius Berner, Chao Liu, Arash Vahdat, Weili Nie, Xinchao Wang (2026). Flex-Forcing: Towards a Unified Autoregressive and Bidirectional Video Diffusion Model. International Conference on Machine Learning (ICML).

arXiv

Subham Sekhar Sahoo, Zhihan Yang, Yash Akhauri, Johnna Liu, Deepansha Singh, Zhoujun Cheng, Zhengzhong Liu, Eric Xing, John Thickstun, Arash Vahdat (2026). Esoteric Language Models: A Family of Any-Order Diffusion LLMs. International Conference on Machine Learning (ICML).

arXiv

Weili Nie, Julius Berner, Nanye Ma, Chao Liu, Saining Xie, Arash Vahdat (2026). Transition Matching Distillation for Fast Video Generation. IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

arXiv

Kieran Didi, Zuobai Zhang, Guoqing Zhou, Danny Reidenbach, Zhonglin Cao, Sooyoung Cha, Tomas Geffner, Christian Dallago, Jian Tang, Michael M. Bronstein, Martin Steinegger, Emine Kucukbenli, Arash Vahdat, Karsten Kreis (2026). Scaling Atomistic Protein Binder Design with Generative Pretraining and Test-Time Compute. International Conference on Learning Representations (ICLR).

arXiv

Tomas Geffner, Kieran Didi, Zhonglin Cao, Danny Reidenbach, Zuobai Zhang, Christian Dallago, Emine Kucukbenli, Karsten Kreis, Arash Vahdat (2026). La-Proteina: Atomistic Protein Generation via Partially Latent Flow Matching. International Conference on Learning Representations (ICLR).

arXiv

Seul Lee, Karsten Kreis, Srimukh Prasad Veccham, Meng Liu, Danny Reidenbach, Saee Gopal Paliwal, Weili Nie, Arash Vahdat (2026). Exploring Synthesizable Chemical Space with Iterative Pathway Refinements. International Conference on Learning Representations (ICLR).

arXiv

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

arXiv

Vignav Ramesh, Morteza Mardani (2025). Test-Time Scaling of Diffusion Models via Noise Trajectory Search. Advances in Neural Information Processing Systems (NeurIPS).

arXiv

Salva Rühling Cachay, Miika Aittala, Karsten Kreis, Noah Brenowitz, Arash Vahdat, Morteza Mardani, Rose Yu (2025). Elucidated Rolling Diffusion Models for Probabilistic Forecasting of Complex Dynamics. Advances in Neural Information Processing Systems (NeurIPS).

arXiv

Danny Reidenbach, Zhonglin Cao, Zuobai Zhang, Kieran Didi, Tomas Geffner, Guoqing Zhou, Jian Tang, Christian Dallago, Arash Vahdat, Emine Kucukbenli, Karsten Kreis (2025). Consistent Synthetic Sequences Unlock Structural Diversity in Fully Atomistic De Novo Protein Design. ArXiv Preprint.

arXiv

Amirmojtaba Sabour, Sanja Fidler, Karsten Kreis (2025). Align Your Flow: Scaling Continuous-Time Flow Map Distillation. Advances in Neural Information Processing Systems (NeurIPS).

arXiv

Seul Lee, Karsten Kreis, Srimukh Prasad Veccham, Meng Liu, Danny Reidenbach, Yuxing Peng, Saee Paliwal, Weili Nie, Arash Vahdat (2025). GenMol: A Drug Discovery Generalist with Discrete Diffusion. International Conference on Machine Learning (ICML).

arXiv

Stathi Fotiadis, Noah Brenowitz, Tomas Geffner, Yair Cohen, Mike Pritchard, Arash Vahdat, Morteza Mardani (2025). Adaptive Flow Matching for Resolving Small-Scale Physics. International Conference on Machine Learning (ICML).

arXiv

Weixi Feng, Chao Liu, Sifei Liu, William Yang Wang, Arash Vahdat, Weili Nie (2025). BlobGEN-Vid: Compositional Text-to-Video Generation with Blob Video Representations. IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

arXiv

Sangyun Lee, Yilun Xu, Tomas Geffner, Giulia Fanti, Karsten Kreis, Arash Vahdat, Weili Nie (2025). Truncated Consistency Models. International Conference on Learning Representations (ICLR).

arXiv

Sulin Liu, Juno Nam, Andrew Campbell, Hannes Stark, Yilun Xu, Tommi Jaakkola, Rafael Gomez-Bombarelli (2025). Think while You Generate: Discrete Diffusion with Planned Denoising. International Conference on Learning Representations (ICLR).

arXiv

Zizheng Pan, Bohan Zhuang, De-an Huang, Weili Nie, Zhiding Yu, Chaowei Xiao, Jianfei Cai, Anima Anandkumar (2025). T-Stitch: Accelerating Sampling in Pre-Trained Diffusion Models with Trajectory Stitching. International Conference on Learning Representations (ICLR).

arXiv

Nicolas Zilberstein, Morteza Mardani, Santiago Segarra (2025). Repulsive Latent Score Distillation for Solving Inverse Problems. International Conference on Learning Representations (ICLR).

arXiv

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

arXiv

Hannes Stark, Bowen Jing, Tomas Geffner, Jason Yim, Tommi Jaakkola, Arash Vahdat, Karsten Kreis (2025). ProtComposer: Compositional Protein Structure Generation with 3D Ellipsoids. International Conference on Learning Representations (ICLR).

arXiv

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

arXiv

Kushagra Pandey, Jaideep Pathak, Yilun Xu, Stephan Mandt, Mike Pritchard, Arash Vahdat, Morteza Mardani (2025). Heavy-Tailed Diffusion Models. International Conference on Learning Representations (ICLR).

arXiv

Minkai Xu, Tomas Geffner, Karsten Kreis, Weili Nie, Yilun Xu, Jure Leskovec, Stefano Ermon, Arash Vahdat (2025). Energy-based Diffusion Language Models for Text Generation. International Conference on Learning Representations (ICLR).

arXiv

Morteza Mardani, Noah Brenowitz, Yair Cohen, Jaideep Pathak, Chieh-Yu Chen, Cheng-Chin Liu, Arash Vahdat, Mohammad Amin Nabian, Tao Ge, Akshay Subramaniam, Karthik Kashinath, Jan Kautz, Mike Pritchard (2025). Residual corrective diffusion modeling for km-scale atmospheric downscaling. Nature Communications Earth & Environment.

arXiv

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 (2025). Score-Based Diffusion Models in Function Space. Journal of Machine Learning Research.

arXiv

Marc T. Law, Karsten Kreis, Haggai Maron (2025). Directed Graph Generation with Heat Kernels. Transactions on Machine Learning Research.

Giannis Daras, Weili Nie, Karsten Kreis, Alex Dimakis, Morteza Mardani, Nikola Kovachki, Arash Vahdat (2024). Warped Diffusion: Solving Video Inverse Problems with Image Diffusion Models. Advances in Neural Information Processing Systems (NeurIPS).

arXiv

Seul Lee, Karsten Kreis, Srimukh Prasad Veccham, Meng Liu, Danny Reidenbach, Saee Paliwal, Arash Vahdat, Weili Nie (2024). Molecule Generation with Fragment Retrieval Augmentation. Advances in Neural Information Processing Systems (NeurIPS).

arXiv

Jiawei Ren, Kevin Xie, Ashkan Mirzaei, Hanxue Liang, Xiaohui Zeng, Karsten Kreis, Ziwei Liu, Antonio Torralba, Sanja Fidler, Seung Wook Kim, Huan Ling (2024). L4GM: Large 4D Gaussian Reconstruction Model. Advances in Neural Information Processing Systems (NeurIPS).

arXiv

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

arXiv

Chao Liu, Weili Nie, Sifei Liu, Abhishek Badki, Hang Su, Morteza Mardani, Benjamin Eckart, Arash Vahdat (2024). BlobGEN-3D: Compositional 3D-Consistent Freeview Image Generation with 3D Blobs. ACM Transactions on Graphics (SIGGRAPH ASIA).

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

arXiv

Dejia Xu, Ye Yuan, Morteza Mardani, Sifei Liu, Jiaming Song, Zhangyang Wang, Arash Vahdat (2024). AGG: Amortized Generative 3D Gaussians for Single Image to 3D. Transactions on Machine Learning Research.

arXiv

Ali Hatamizadeh, Jiaming Song, Guilin Liu, Jan Kautz, Arash Vahdat (2024). DiffiT: Diffusion Vision Transformers for Image Generation. European Conference on Computer Vision (ECCV).

arXiv

Yilun Xu, Gabriele Corso, Tommi Jaakkola, Arash Vahdat, Karsten Kreis (2024). DisCo-Diff: Enhancing Continuous Diffusion Models with Discrete Latents. International Conference on Machine Learning (ICML).

arXiv

Weili Nie, Sifei Liu, Morteza Mardani, Chao Liu, Benjamin Eckart, Arash Vahdat (2024). Compositional Text-to-Image Generation with Dense Blob Representations. International Conference on Machine Learning (ICML).

arXiv

Amirmojtaba Sabour, Sanja Fidler, Karsten Kreis (2024). Align Your Steps: Optimizing Sampling Schedules in Diffusion Models. International Conference on Machine Learning (ICML).

arXiv

Dongsu Zhang, Francis Williams, Zan Gojcic, Karsten Kreis, Sanja Fidler, Young Min Kim, Amlan Kar (2024). Outdoor Scene Extrapolation with Hierarchical Generative Cellular Automata. IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

arXiv

Huan Ling, Seung Wook Kim, Antonio Torralba, Sanja Fidler, Karsten Kreis (2024). Align Your Gaussians: Text-to-4D with Dynamic 3D Gaussians and Composed Diffusion Models. IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

arXiv

Yufeng Zheng, Xueting Li, Koki Nagano, Sifei Liu, Karsten Kreis, Otmar Hilliges, Shalini De Mello (2024). A Unified Approach for Text- and Image-guided 4D Scene Generation. IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

arXiv

Katja Schwarz, Seung Wook Kim, Jun Gao, Sanja Fidler, Andreas Geiger, Karsten Kreis (2024). WildFusion: Learning 3D-Aware Latent Diffusion Models in View Space. International Conference on Learning Representations (ICLR).

arXiv

Yichen Li, Yilun Du, Chao Liu, Francis Williams, Michael Foshey, Benjamin Eckart, Jan Kautz, Joshua B. Tenenbaum, Antonio Torralba, Wojciech Matusik (2024). Learning to Jointly Understand Visual and Tactile Signals. International Conference on Learning Representations (ICLR).

Sihyun Yu, Weili Nie, De-an Huang, Boyi Li, Jinwoo Shin, Anima Anandkumar (2024). Efficient Video Diffusion Models via Content-Frame Motion-Latent Decomposition. International Conference on Learning Representations (ICLR).

arXiv

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

arXiv

Hongkai Zheng, Weili Nie, Arash Vahdat, Anima Anandkumar (2024). Fast Training of Diffusion Models with Masked Transformers. Transactions on Machine Learning Research.

arXiv

Zhuolin Yang, Wei Ping, Zihan Liu, Vijay Korthikanti, Weili Nie, De-an Huang, Linxi Fan, Zhiding Yu, Shiyi Lan, Bo Li, Ming-Yu Liu, Yuke Zhu, Mohammad Shoeybi, Bryan Catanzaro, Chaowei Xiao, Anima Anandkumar (2023). Re-ViLM: Retrieval-Augmented Visual Language Model for Zero and Few-Shot Image Captioning. Findings of the Association for Computational Linguistics: EMNLP.

arXiv

Tianshi Cao, Karsten Kreis, Sanja Fidler, Nicholas Sharp, Kangxue Yin (2023). TexFusion: Synthesizing 3D Textures with Text-Guided Image Diffusion Models. IEEE International Conference on Computer Vision (ICCV).

arXiv

Batu Ozturkler, Chao Liu, Benjamin Eckart, Morteza Mardani, Jiaming Song, Jan Kautz (2023). SMRD: SURE-based Robust MRI Reconstruction with Diffusion Models. International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI).

arXiv

Ye Yuan, Jiaming Song, Umar Iqbal, Arash Vahdat, Jan Kautz (2023). PhysDiff: Physics-Guided Human Motion Diffusion Model. IEEE International Conference on Computer Vision (ICCV).

arXiv

Daiqing Li, Huan Ling, Amlan Kar, David Acuna, Seung Wook Kim, Karsten Kreis, Antonio Torralba, Sanja Fidler (2023). DreamTeacher: Pretraining Image Backbones with Deep Generative Models. IEEE International Conference on Computer Vision (ICCV).

arXiv

Tim Dockhorn, Tianshi Cao, Arash Vahdat, Karsten Kreis (2023). Differentially Private Diffusion Models. Transactions on Machine Learning Research.

arXiv

Alexander Trevithick, Matthew Chan, Michael Stengel, Eric Ryan Chan, Chao Liu, Zhiding Yu, Sameh Khamis, Manmohan Chandraker, Ravi Ramamoorthi, Koki Nagano (2023). Real-Time Radiance Fields for Single-Image Portrait View Synthesis. ACM Transactions on Graphics (SIGGRAPH).

arXiv

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

Guan-Horng Liu, Arash Vahdat, De-an Huang, Evangelos Theodorou, Weili Nie, Anima Anandkumar (2023). I^2SB: Image-to-Image Schrödinger Bridge. International Conference on Machine Learning (ICML).

arXiv

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

arXiv

Davis Rempe, Zhengyi Luo, Xue Bin Peng, Ye Yuan, Kris Kitani, Karsten Kreis, Sanja Fidler, Or Litany (2023). Trace and Pace: Controllable Pedestrian Animation via Guided Trajectory Diffusion. IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

arXiv

Paul Micaelli, Pavlo Molchanov, Arash Vahdat, Hongxu Yin, Jan Kautz (2023). Recurrence without Recurrence: Stable Video Landmark Detection with Deep Equilibrium Models. IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

arXiv

Jiarui Xu, Sifei Liu, Arash Vahdat, Wonmin Byeon, Xiaolong Wang, Shalini De Mello (2023). Open-Vocabulary Panoptic Segmentation with Text-to-Image Diffusion Models. IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

arXiv

Seung Wook Kim, Bradley Brown, Kangxue Yin, Karsten Kreis, Katja Schwarz, Daiqing Li, Robin Rombach, Antonio Torralba, Sanja Fidler (2023). NeuralField-LDM: Scene Generation with Hierarchical Latent Diffusion Models. IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

arXiv

Chen-Hsuan Lin, Jun Gao, Luming Tang, Towaki Takikawa, Xiaohui Zeng, Xun Huang, Karsten Kreis, Sanja Fidler, Ming-Yu Liu, Tsung-Yi Lin (2023). Magic3D: High-Resolution Text-to-3D Content Creation. IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

arXiv

Andreas Blattmann, Robin Rombach, Huan Ling, Tim Dockhorn, Seung Wook Kim, Sanja Fidler, Karsten Kreis (2023). Align your Latents: High-Resolution Video Synthesis with Latent Diffusion Models. IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

arXiv

Jiaming Song, Arash Vahdat, Morteza Mardani, Jan Kautz (2023). Pseudoinverse-Guided Diffusion Models for Inverse Problems. International Conference on Learning Representations (ICLR).

Chao Liu, Benjamin Eckart, Jan Kautz (2023). Online Consistent Video Depth using Continuous Geometric Representations. International Conference on Robotics and Automation (ICRA).

Manli Shu, Weili Nie, De-an Huang, Zhiding Yu, Tom Goldstein, Anima Anandkumar, Chaowei Xiao (2022). Test-time prompt tuning for zero-shot generalization in vision-language models. Advances in Neural Information Processing Systems (NeurIPS).

arXiv

Xiaohui Zeng, Arash Vahdat, Francis Williams, Zan Gojcic, Or Litany, Sanja Fidler, Karsten Kreis (2022). LION: Latent Point Diffusion Models for 3D Shape Generation. Advances in Neural Information Processing Systems (NeurIPS).

arXiv

Tim Dockhorn, Arash Vahdat, Karsten Kreis (2022). GENIE: Higher-Order Denoising Diffusion Solvers. Advances in Neural Information Processing Systems (NeurIPS).

arXiv

Pavlo Molchanov, Jimmy Hall, Hongxu Yin, Jan Kautz, Nicolo Fusi, Arash Vahdat (2022). LANA: Latency Aware Network Acceleration. European Conference on Computer Vision (ECCV).

arXiv

Weili Nie, Brandon Guo, Yujia Huang, Chaowei Xiao, Arash Vahdat, Anima Anandkumar (2022). Diffusion Models for Adversarial Purification. International Conference on Machine Learning (ICML).

arXiv

Hongxu Yin, Arash Vahdat, Jose M. Alvarez, Arun Mallya, Jan Kautz, Pavlo Molchanov (2022). A-ViT: Adaptive Tokens for Efficient Vision Transformer. IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

arXiv

Zhisheng Xiao, Karsten Kreis, Arash Vahdat (2022). Tackling the Generative Learning Trilemma with Denoising Diffusion GANs. International Conference on Learning Representations (ICLR).

arXiv

Tim Dockhorn, Arash Vahdat, Karsten Kreis (2022). Score-Based Generative Modeling with Critically-Damped Langevin Diffusion. International Conference on Learning Representations (ICLR).

arXiv

Ben Wu, Chao Liu, Benjamin Eckart, Jan Kautz (2022). Neural Interferometry: Image Reconstruction from Astronomical Interferometers using Transformer-Conditioned Neural Fields. AAAI Conference on Artificial Intelligence (AAAI).

Arash Vahdat, Karsten Kreis, Jan Kautz (2021). Score-based Generative Modeling in Latent Space. Advances in Neural Information Processing Systems (NeurIPS).

arXiv

Tianshi Cao, Alex Bie, Arash Vahdat, Sanja Fidler, Karsten Kreis (2021). Don't Generate Me: Training Differentially Private Generative Models with Sinkhorn Divergence. Advances in Neural Information Processing Systems (NeurIPS).

arXiv

Weili Nie, Arash Vahdat, Anima Anandkumar (2021). Controllable and Compositional Generation with Latent-Space Energy-Based Models. Advances in Neural Information Processing Systems (NeurIPS).

arXiv

Jyoti Aneja, Alexander Schwing, Jan Kautz, Arash Vahdat (2021). A Contrastive Learning Approach for Training Variational Autoencoder Priors. Advances in Neural Information Processing Systems (NeurIPS).

arXiv

Benjamin Eckart, Wentao Yuan, Chao Liu, Jan Kautz (2021). Self-Supervised Learning on 3D Point Clouds by Learning Discrete Generative Models. IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

Hongxu Yin, Arun Mallya, Arash Vahdat, Jose M. Alvarez, Jan Kautz, Pavlo Molchanov (2021). See through Gradients: Image Batch Recovery via GradInversion. IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

arXiv

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

arXiv

Jeremy Bernstein, Arash Vahdat, Yisong Yue, Ming-Yu Liu (2020). On the Distance between Two Neural Networks and the Stability of Learning. Advances in Neural Information Processing Systems (NeurIPS).

arXiv

Arash Vahdat, Jan Kautz (2020). NVAE: A Deep Hierarchical Variational Autoencoder. Advances in Neural Information Processing Systems (NeurIPS).

arXiv

Morteza Mardani, Guilin Liu, Aysegul Dundar, Shiqiu Liu, Andrew Tao, Bryan Catanzaro (2020). Neural FFTs for Universal Texture Image Synthesis. Advances in Neural Information Processing Systems (NeurIPS).

Tanmay Gupta, Arash Vahdat, Gal Chechik, Xiaodong Yang, Jan Kautz, Derek Hoiem (2020). Contrastive Learning for Weakly Supervised Phrase Grounding. European Conference on Computer Vision (ECCV).

arXiv

Arash Vahdat, Evgeny Andriyash, William G Macready (2020). Undirected Graphical Models as Approximate Posteriors. International Conference on Machine Learning (ICML).

arXiv

Arash Vahdat, Arun Mallya, Ming-Yu Liu, Jan Kautz (2020). UNAS: Differentiable Architecture Search Meets Reinforcement Learning. IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

arXiv

Mostafa S. Ibrahim, Arash Vahdat, Mani Ranjbar, William G. Macready (2020). Semi-Supervised Semantic Image Segmentation with Self-correcting Networks. IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

arXiv