Publications

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

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2023

Tree-structured Policy Planning with Learned Behavior Models
Yuxiao Chen, Peter Karkus, Boris Ivanovic, Xinshuo Weng, Marco Pavone
Guided Conditional Diffusion for Controllable Traffic Simulation
Ziyuan Zhong, Davis Rempe, Danfei Xu, Yuxiao Chen, Sushant Veer, Gerry Che, Baishakhi Ray, Marco Pavone
Expanding the Deployment Envelope of Behavior Prediction via Adaptive Meta-Learning
Boris Ivanovic, James Harrison, Marco Pavone
BITS: Bi-level Imitation for Traffic Simulation
Danfei Xu, Yuxiao Chen, Boris Ivanovic, Marco Pavone
ProgPrompt: Generating Situated Robot Task Plans Using Large Language Models
Ishika Singh, Valts Blukis, Arsalan Mousavian, Ankit Goyal, Danfei Xu, Jonathan Tremblay, Dieter Fox, Jesse Thomason, Animesh Garg
Global and Reactive Motion Generation with Geometric Fabric Command Sequences
Weiming Zhi, Iretiayo Akinola, Karl Van Wyk, Nathan Ratliff, Fabio Ramos
Parallel Inversion of Neural Radiance Fields for Robust Pose Estimation
Yunzhi Lin, Thomas Müller, Jonathan Tremblay, Bowen Wen, Stephen Tyree, Alex Evans, Patricio A. Vela, Stan Birchfield
The Best Defense is a Good Offense: Adversarial Augmentation against Adversarial Attacks
Iuri Frosio, Jan Kautz
Subpixel Deblurring of Anti-Aliased Raster Clip Art
Jinfan Yang, Nicholas Vining, Shakiba Kheradmand, Nathan Carr, Leonid Sigal, Alla Sheffer
CabiNet: Scaling Neural Collision Detection for Object Rearrangement with Procedural Scene Generation
Adithya Murali, Arsalan Mousavian, Clemens Eppner, Adam Fishman, Dieter Fox
Recursive Control Variates for Inverse Rendering
Baptiste Nicolet, Fabrice Rousselle, Jan Novák, Alexander Keller, Wenzel Jakob, Thomas Müller
CALM: Conditional Adversarial Latent Models for Directable Virtual Characters
Chen Tessler, Yoni Kasten, Yunrong Guo, Shie Mannor, Gal Chechik, Xue Bin Peng
Real-Time Neural Appearance Models
Tizian Zeltner, Fabrice Rousselle, Andrea Weidlich, Petrik Clarberg, Jan Novák, Benedikt Bitterli, Alex Evans, Tomáš Davidovič, Simon Kallweit, Aaron Lefohn
GPViT: A High Resolution Non-Hierarchical Vision Transformer with Group Propagation
Chenhongyi Yang, Jiarui Xu, Shalini De Mello, Elliot J. Crowley, Xiaolong Wang
Notable top 25%
Oral
Robust and Controllable Object-Centric Learning through Energy-based Models
Ruixiang Zhang, Gerry Che, Boris Ivanovic, Renhao Wang, Marco Pavone, Yoshua Bengio, Liam Paull
Reinforcement Learning Guided Detailed Routing for Custom Circuits
Hao Chen, Kai-Chieh Hsu, Walker Turner, Po-Hsuan Wei, Keren Zhu, David Z. Pan, Haoxing (Mark) Ren
DREAM-GAN: Advancing DREAMPlace towards Commercial-Quality using Generative Adversarial Learning
Yi-Chen Lu, Haoxing (Mark) Ren, Hao-Hsiang Hsiao, Sung Kyu Lim
NVCell 2: Routability-Driven Standard Cell Layout in Advanced Nodes with Lattice Graph Routability Model
Chia-Tung (Mark) Ho, Alvin Ho, Matt Fojtik, Minsoo Kim, Shang Wei, Yaguang LI, Brucek Khailany, Haoxing (Mark) Ren
AutoDMP: Automated DREAMPlace-based Macro Placement
Anthony Agnesina, Puranjay Rajvanshi, Tian Yang, Geraldo Pradipta, Austin Jiao, Ben Keller, Brucek Khailany, Haoxing (Mark) Ren
Joint Neural Denoising of Surfaces and Volumes
Nikolai Hofmann, Jon Hasselgren, Jacob Munkberg
Equivariant Architectures for Learning in Deep Weight Spaces
Aviv Navon, Aviv Shamsian, Idan Achituve, Ethan Fetaya, Gal Chechik, Haggai Maron
Enabling Scalable AI Computational Lithography with Physics-Inspired Models
Haoyu Yang, Haoxing (Mark) Ren
Target-free Text-guided Image Manipulation
Wan-Cyuan Fan, Cheng-Fu Yang, Chiao-An Yang, Frank Wang
Frido: Feature Pyramid Diffusion for Complex Scene Image Synthesis
Wan-Cyuan Fan, Yen-Chun Chen, Dongdong Chen, Yu Cheng, Lu Yuan, Frank Wang
A 95.6-TOPS/W Deep Learning Inference Accelerator With Per-Vector Scaled 4-bit Quantization in 5 nm
Ben Keller, Rangharajan Venkatesan, Steve Dai, Stephen Tell, Brian Zimmer, Charbel Sakr, William Dally, Tom Gray, Brucek Khailany
Never Worse, Mostly Better: Stable Policy Improvement in Deep Reinforcement Learning
Pranav Khanna, Guy Tennenholtz, Nadav Merlis, Shie Mannor, Chen Tessler
Self-Supervised Pyramid Representation Learning for Multi-Label Visual Analysis and Beyond
Cheng-Yen Hsieh, Chih-Jung Chang, Fu-En Yang, Frank Wang