Publications

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

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2019

DREAMPlace: Deep Learning Toolkit-Enabled GPU Acceleration for Modern VLSI Placement
Yibo Lin, Shounak Dhar, Wuxi Li, Haoxing (Mark) Ren, Brucek Khailany, David Z. Pan
DAC 2019 Best Paper Award
High Performance Graph Convolutional Networks with Applications in Testability Analysis
Yuzhe Ma, Haoxing (Mark) Ren, Brucek Khailany, Harbinder Sikka, Lijuan Luo, Karthikeyan Natarajan, Bei Yu
PRIMAL: Power Inference using Machine Learning
Yuan Zhou, Haoxing (Mark) Ren, Yanqing Zhang, Ben Keller, Brucek Khailany, Zhiru Zhang
Analog/Mixed-Signal Hardware Error Modeling for Deep Learning Inference
Angad S. Rekhi, Brian Zimmer, Nikola Nedovic, Nigxi Liu, Rangharajan Venkatesan, Miaorong Wang, Brucek Khailany, William Dally, Tom Gray
Buddy Compression: Enabling Larger Memory for Deep Learning and HPC Workloads on GPUs
Esha Choukse, Michael B. Sullivan, Mike O'Connor, Mattan Erez, Jeff Pool, David Nellans, Stephen W. Keckler
DeLTA: GPU Performance Model for Deep Learning Applications with In-depth Memory System Traffic Analysis
Sankug Lym, Donghyuk Lee, Niladrish Chatterjee, Mike O'Connor, Mattan Erez
Routability-Driven Macro Placement with Embedded CNN-Based Prediction Model
Yu-Hung Huang, Zhiyao Xie, Guan-Qi Fang, Tao-Chun Yu, Haoxing (Mark) Ren, Shao-Yun Fang, Yiran Chen, Jiang Hu
Timeloop: A Systematic Approach to DNN Accelerator Evaluation
Angshuman Parashar, Priyanka Raina, Yakun Sophia Shao, Yu-Hsin Chen, Victor A. Ying, Anurag Mukkara, Rangharajan Venkatesan, Brucek Khailany, Steve Keckler, Joel Emer
Informative Object Annotations: Tell Me Something I Don't Know
Lior Bracha, Gal Chechik
Rethinking full connectivity in recurrent neural networks
Matthijs Van keirsbilck, Alex Keller, Xiaodong Yang
Metaoptimization on a Distributed System for Deep Reinforcement Learning
Greg Heinrich, Iuri Frosio
Unsupervised Stylish Image Description Generation via Domain Layer Norm
Cheng-Kuan Chen, Zhu-Feng Pan, Ming-Yu Liu, Min Sun
Models Matter, So Does Training: An Empirical Study of CNNs for Optical Flow Estimation
Deqing Sun, Xiaodong Yang, Ming-Yu Liu, Jan Kautz
A Fusion Approach for Multi-Frame Optical Flow Estimation
Zhile Ren, Orazio Gallo, Deqing Sun, Ming-Hsuan Yang, Erik B. Sudderth, Jan Kautz

2018

Learning towards Minimum Hyperspherical Energy
Weiyang Liu, Rongmei Lin, Zhen Liu, Lixin Liu, Zhiding Yu, Bo Dai, Le Song
Mapping Images to Scene Graphs with Permutation-Invariant Structured Prediction
Roei Herzig, Moshiko Raboh, Gal Chechik, Jonathan Berant, Amir Globerson
Exascale Deep Learning for Climate Analytics
Thorsten Kurth, Sean Treichler, Joshua Romero, Mayur Mudigonda, Nathan Luehr, Everett Phillips, Ankur Mahesh, Michael Matheson, Jack Deslippe, Massimiliano Fatica, Prabhat, Michael Houston
RouteNet: Routability Prediction for Mixed-size Designs using Convolutional Neural Network
Zhiyao Xie, Yu-Hung Huang, Guan-Qi Fang, Haoxing (Mark) Ren, Shao-Yun Fang, Yiran Chen, Hu Jiang
Hand Pose Estimation via Latent 2.5 D Heatmap Regression
Umar Iqbal, Pavlo Molchanov, Thomas Breuel, Juergen Gall, Jan Kautz
Tackling 3D ToF Artifacts Through Learning and the FLAT Dataset
Qi Guo, Iuri Frosio, Orazio Gallo, Todd Zickler, Jan Kautz
Learning Rigidity in Dynamic Scenes with a Moving Camera for 3D Motion Field Estimation
Zhaoyang Lv, Kihwan Kim, Alejandro Troccoli, Deqing Sun, James M. Rehg, Jan Kautz
Domain Adaptation for Semantic Segmentation via Class-Balanced Self-Training
Yang Zou, Zhiding Yu, B. V. K. Vijaya Kumar, Jinsong Wang
Image Inpainting for Irregular Holes Using Partial Convolutions
Guilin Liu, Fitsum A. Reda, Kevin Shih, Ting-Chun Wang, Andrew Tao, Bryan Catanzaro
Switchable Temporal Propagation Network
Sifei Liu, Guangyu Zhong, Shalini De Mello, Jinwei Gu, Varun Jampani
Multimodal Unsupervised Image-to-Image Translation
Xun Huang, Ming-Yu Liu, Serge Belongie, Jan Kautz
A Closed-form Solution to Photorealistic Image Stylization
Yijun Li, Ming-Yu Liu, Xueting Li, Ming-Hsuan Yang, Jan Kautz
Superpixel Sampling Networks
Varun Jampani, Deqing Sun, Ming-Yu Liu, Ming-Hsuan Yang, Jan Kautz
Machine Learning and Rendering
Alex Keller, Jaroslav Křivánek, Jan Novák, Anton Kaplanyan, Marco Salvi
Noise2Noise: Learning Image Restoration without Clean Data
Jaakko Lehtinen, Jacob Munkberg, Jon Hasselgren, Samuli Laine, Tero Karras, Miika Aittala, Timo Aila
Light-weight Head Pose Invariant Gaze Tracking
Rajeev Ranjan, Shalini De Mello, Jan Kautz
Best Paper (runner up) Workshop on Analysis and Modeling of Faces and Gestures
MoCoGAN: Decomposing Motion and Content for Video Generation
Sergey Tulyakov, Ming-Yu Liu, Xiaodong Yang, Jan Kautz
Depth-Based 3D Hand Pose Estimation: From Current Achievements to Future Goals
Shanxin Yuan, Guillermo Garcia-Hernando, Bjorn Stenger, Pavlo Molchanov, Jan Kautz, Sina Honari