Publications

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

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2020

Analyzing and Improving the Image Quality of StyleGAN
Tero Karras, Samuli Laine, Miika Aittala, Janne Hellsten, Jaakko Lehtinen, Timo Aila
Novel View Synthesis of Dynamic Scenes with Globally Coherent Depths
Jae shin Yoon, Kihwan Kim, Orazio Gallo, Hyunsoo Park, Jan Kautz
Two-shot Spatially-varying BRDF and Shape Estimation
Mark Boss, Varun Jampani, Kihwan Kim, Hendrik P.A. Lensch, Jan Kautz
Self-Supervised Viewpoint Learning From Image Collections
Siva Karthik Mustikovela, Varun Jampani, Shalini De Mello, Sifei Liu, Umar Iqbal, Carsten Rother, Jan Kautz
Making Convolutions Resilient via Algorithm-Based Error Detection Techniques
Siva Hari, Michael B. Sullivan, Timothy Tsai, Steve Keckler
Learning Canonical Representations for Scene Graph to Image Generation
Roei Herzig, Amir Bar, Huijuan Xu, Gal Chechik, Trevor Darrell, Amir Globerson
Buddy Compression: Enabling Larger Memory for Deep Learning and HPC Workloads on GPUs
Esha Chouske, Michael B. Sullivan, Mike O'Connor, Mattan Erez, Jeff Pool, David Nellans, Steve Keckler
Self-supervised 6D Object Pose Estimation for Robot Manipulation
Xinke Deng, Yu Xiang, Arsalan Mousavian, Clemens Eppner, Timothy Bretl, Dieter Fox
An In-Network Architecture for Accelerating Shared-Memory Multiprocessor Collectives
Benjamin Klenk, Ted Jiang, Greg Thorson, Larry Dennison
How to close sim-real gap? transfer with segmentation!
Mengyuan Yan, Qingyun Sun, Iuri Frosio, Stephen Tyree, Jan Kautz
ML-driven Malware that Targets AV Safety
Saurabh Jha, Shengkun Cui, Subho S. Banerjee, James Cyriac, Timothy Tsai, Zbigniew T. Kalbarczyk, Ravishankar K. Iyer
MAESTRO: A Data-Centric Approach to Understand Reuse, Performance, and Hardware Cost of DNN Mappings
Hyoukjun Kwon, Prasanth Chatarasi, Vivek Sarkar, Tushar Krishna, Michael Pellauer, Angshuman Parashar
Genome Variant Calling with a Deep Averaging Network
Nikolai Yakovenko, Avantika Lal, Johnny Israeli, Bryan Catanzaro
SymGAN: Orientation Estimation without Annotation for Symmetric Objects
Phil Ammirato, Jonathan Tremblay, Ming-Yu Liu, Alexander Berg, Dieter Fox
Neurreg: Neural registration and its application to image segmentation
Wentao Zhu, Andriy Myronenko, Ziyue Xu, Wenqi Li, Holger Roth, Yufang Huang, Fausto Milletari, Daguang Xu
HarDNN: Feature Map Vulnerability Evaluation in CNNs
Abdulrahman Mahmoud, Siva Hari, Christopher W. Fletcher, Sarita V. Adve, Charbel Sakr, Naresh Shanbhag, Pavlo Molchanov, Michael B. Sullivan, Timothy Tsai, Steve Keckler
On the Distance between Two Neural Networks and the Stability of Learning
Jeremy Bernstein, Arash Vahdat, Yisong Yue, Ming-Yu Liu
Domain Stylization: A Fast Covariance Matching Framework towards Domain Adaptation
Aysegul Dundar, Ming-Yu Liu, Zhiding Yu, Ting-Chun Wang, John Zedlewski, Jan Kautz
A 0.32–128 TOPS, Scalable Multi-Chip-Module-Based Deep Neural Network Inference Accelerator With Ground-Referenced Signaling in 16 nm
Brian Zimmer, Rangharajan Venkatesan, Yakun Sophia Shao, Jason Clemons, Matt Fojtik, Ted Jiang, Ben Keller, Alicia Klinefelter, Nathaniel Pinckney, Priyanka Raina, Stephen Tell, Yanqing Zhang, William Dally, Joel Emer, Tom Gray, Steve Keckler, Brucek Khailany
JSSC 2020 Best Paper award
FIST: A Feature-Importance Sampling and Tree-Based Method for Automatic Design Flow Parameter Tuning
Zhiyao Xie, Guan-Qi Fang, Yu-Hung Huang, Mark Haoxing Ren, Yanqing Zhang, Brucek Khailany, Shao-Yun Fang, Jiang Hu, Yiran Chen, Erick Carvajal Barboza
PowerNet: Transferable Dynamic IR Drop Estimation via Maximum Convolutional Neural Network
Zhiyao Xie, Mark Haoxing Ren, Brucek Khailany, Ye Sheng, Santosh Santosh, Jiang Hu, Yiran Chen

2019

Few-Shot Video-to-Video Synthesis
Ting-Chun Wang, Ming-Yu Liu, Andrew Tao, Guilin Liu, Jan Kautz, Bryan Catanzaro
Dance to Music
Hsin-Ying Lee, Xiaodong Yang, Ming-Yu Liu, Ting-Chun Wang, Yu-Ding Lu, Ming-Hsuan Yang, Jan Kautz
High-Quality Self-Supervised Deep Image Denoising
Samuli Laine, Tero Karras, Jaakko Lehtinen, Timo Aila
Improved Precision and Recall Metric for Assessing Generative Models
Tuomas Kynkäänniemi, Tero Karras, Samuli Laine, Jaakko Lehtinen, Timo Aila
Instant Quantization of neural networks using Monte Carlo Methods
Gonçalo Mordido, Matthijs Van keirsbilck, Alex Keller
Joint Optimization for Cooperative Image Captioning
Gilad Vered, Gal Oren, Yuval Atzmon, Gal Chechik
MAGNet: A Modular Accelerator Generator for Neural Networks
Rangharajan Venkatesan, Sophia Shao, Miaorong Wang, Jason Clemons, Steve Dai, Matt Fojtik, Ben Keller, Alicia Klinefelter, Nathaniel Pinckney, Priyanka Raina, Yanqing Zhang, Brian Zimmer, William Dally, Joel Emer, Steve Keckler, Brucek Khailany
Highly-scalable, Physics-informed GANs for Learning Solutions of Stochastic PDEs
Liu Yang, Sean Treichler, Thorsten Kurth, Keno Fischer, David Barajas-Solano, Josh Romero, Valentin Churavy, Alexandre Tartakovsky, Michael Houston, Prabhat, George Karniadakis
Neural Inverse Rendering of an Indoor Scene from a Single Image
Soumyadip Sengupta, Jinwei Gu, Kihwan Kim, Guilin Liu, David W. Jacobs, Jan Kautz
Few-Shot Adaptive Gaze Estimation
Seonwook Park, Shalini De Mello, Pavlo Molchanov, Umar Iqbal, Otmar Hilliges, Jan Kautz
Oral
Extreme View Synthesis
Inchang Choi, Orazio Gallo, Alejandro Troccoli, Min H. Kim, Jan Kautz