Publications

Our publications provide insight into some of our leading-edge research.

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2020

Self-Learning Transformations for Improving Gaze and Head Redirection
Yufeng Zheng, Seonwook Park, Xucong Zhang, Shalini De Mello, Otmar Hilliges
A Causal View of Compositional Zero-Shot Recognition
Yuval Atzmon, Felix Kreuk, Uri Shalit, Gal Chechik
Bongard-LOGO: A New Benchmark for Human-Level Concept Learning and Reasoning
Weili Nie, Zhiding Yu, Lei Mao, Ankit B. Patel, Yuke Zhu, Anima Anandkumar
Neural Networks with Recurrent Generative Feedback
Yujia Huang, James Gornet, Sihui Dai, Zhiding Yu, Tan Nguyen, Doris Y. Tsao, Anima Anandkumar
Learning Deformable Tetrahedral Meshes for 3D Reconstruction
Jun Gao, Wenzheng Chen, Tommy Xiang, Clement Fuji Tsang, Alec Jacobson, Morgan McGuire
Convolutional Tensor-Train LSTM for Spatio-Temporal Learning
Jiahao Su, Wonmin Byeon, Jean Kossaifi, Furong Huang, Jan Kautz, Anima Anandkumar
Accelerating Reinforcement Learning through GPU Atari Emulation
Iuri Frosio, Steven Dalton
Training Generative Adversarial Networks with Limited Data
Tero Karras, Miika Aittala, Janne Hellsten, Samuli Laine, Jaakko Lehtinen, Timo Aila
Variational Amodal Object Completion
Huan Ling, David Acuna, Karsten Kreis, Seung Wook Kim, Sanja Fidler
Neural FFTs for Universal Texture Image Synthesis
Morteza Mardani, Guilin Liu, Aysegul Dundar, Shiqiu Liu, Andrew Tao, Bryan Catanzaro
Neural Control Variates
Thomas Müller, Fabrice Rousselle, Alex Keller, Jan Novák
ZEST: Zero-shot Learning from Text Descriptions using Textual Similarity and Visual Summarization
Tzuf Paz-Argaman, Yuval Atzmon, Gal Chechik, Reut Tsarfaty
Generating and Characterizing Scenarios for Safety Testing of Autonomous Vehicles
Zahra Ghodsi, Siva Hari, Iuri Frosio, Timothy Tsai, Alejandro Troccoli, Steve Keckler, Siddharth Garg, Anima Anandkumar
Generating and Characterizing Scenarios for Safety Testing of Autonomous Vehicles
Zahra Ghodsi, Siva Hari, Iuri Frosio, Timothy Tsai, Alejandro Troccoli, Steve Keckler, Siddharth Garg, Anima Anandkumar
Modular Primitives for High-Performance Differentiable Rendering
Samuli Laine, Janne Hellsten, Tero Karras, Yeongho Seol, Jaakko Lehtinen, Timo Aila
Learning Object Permanence from Video
Aviv Shamsian, Ofri Kleinfeld, Amir Globerson, Gal Chechik
A Programmable Approach to Neural Network Compression
Vinu Joseph, Ganesh L. Gopalakrishnan, Saurav Muralidharan, Michael Garland, Animesh Garg
Accelerating Chip Design with Machine Learning
Brucek Khailany, Haoxing (Mark) Ren, Steve Dai, Saad Godil, Ben Keller, Robert Kirby, Alicia Klinefelter, Rangharajan Venkatesan, Yanqing Zhang, Bryan Catanzaro, William Dally
HarDNN: Fine-Grained Vulnerability Evaluation and Protection for Convolutional Neural Networks
Abdulrahman Mahmoud, Siva Hari, Christopher W. Fletcher, Sarita V. Adve, Charbel Sakr, Naresh Shanbhag, Pavlo Molchanov, Michael B. Sullivan, Timothy Tsai, Steve Keckler
UNAS: Differentiable Architecture Search Meets Reinforcement Learning
Arash Vahdat, Arun Mallya, Ming-Yu Liu, Jan Kautz
UFO2: A Unified Framework towards Omni-supervised Object Detection
Zhongzheng Ren, Zhiding Yu, Xiaodong Yang, Ming-Yu Liu, Alexander G. Schwing, Jan Kautz
Joint Disentangling and Adaptation for Cross-Domain Person Re-Identification
Yang Zou, Xiaodong Yang, Zhiding Yu, B. V. K. Vijaya Kumar, Jan Kautz
Weakly-Supervised 3D Hand Pose Estimation via Biomechanical Constraints
Adrian Spurr, Umar Iqbal, Pavlo Molchanov, Otmar Hilliges, Jan Kautz
World-Consistent Video-to-Video Synthesis
Arun Mallya, Ting-Chun Wang, Karan Sapra, Ming-Yu Liu
Self-supervised Single-view 3D Reconstruction via Semantic Consistency
Xueting Li, Sifei Liu, Kihwan Kim, Shalini De Mello, Varun Jampani, Ming-Hsuan Yang, Jan Kautz
ParaGraph: Layout Parasitics and Device Parameter Prediction using Graph Neural Networks
Haoxing (Mark) Ren, George Kokai, Walker Turner, Ting-Sheng Ku
Planaria: Dynamic Architecture Fission for Spatial Multi-Tenant Acceleration of Deep Neural Networks
Soroush Ghodrati, Byung Hoon Ahn, Joon Kyung Kim, Sean Kinzer, Brahmendra Reddy Yatham, Navateja Alla, Hardik Sharma, Mohammad Alian, Eiman Ebrahimi, Nam Sung Kim, Cliff Young, Hadi Esmaeilzadeh
GRANNITE: Graph Neural Network Inference for Transferable Power Estimation
Yanqing Zhang, Haoxing (Mark) Ren, Brucek Khailany
Semi-Supervised StyleGAN for Disentanglement Learning
Weili Nie, Tero Karras, Animesh Garg, Shoubhik Debnath, Anjul Patney, Ankit B. Patel, Anima Anandkumar
Angular Visual Hardness
Beidi Chen, Weiyang Liu, Zhiding Yu, Jan Kautz, Anshumali Shrivastava, Animesh Garg, Anima Anandkumar
Learning Algebraic Multigrid Using Graph Neural Networks
Ilay Luz, Meirav Galun, Haggai Maron, Ronen Basri, Irad Yavneh
On Learning Sets of Symmetric Elements
Haggai Maron, Or Litany, Gal Chechik, Ethan Fetaya
Outstanding Paper, ICML 2020