Publications

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

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2023

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

2022

Task-Relevant Failure Detection for Trajectory Predictors in Autonomous Vehicles
Alec Farid, Sushant Veer, Boris Ivanovic, Karen Leung, Marco Pavone
DiffStack: A Differentiable and Modular Control Stack for Autonomous Vehicles
Peter Karkus, Boris Ivanovic, Shie Mannor, Marco Pavone
Robust Trajectory Prediction against Adversarial Attacks
Yulong Cao, Danfei Xu, Xinshuo Weng, Z. Morely Mao, Anima Anandkumar, Chaowei Xiao, Marco Pavone
Selected for Oral Presentation
Efficient Arithmetic Block Identification with Graph Learning and Network-flow
Ziyi Wang, Zhuolun He, Chen Bai, Haoyu Yang, Bei Yu
Deep Learning-Based Synchronization for Uplink NB-IoT
Fayçal Aït Aoudia , Jakob Hoydis, Sebastian Cammerer, Matthijs Van keirsbilck, Alex Keller
Graph Neural Networks for Channel Decoding
Sebastian Cammerer, Jakob Hoydis, Fayçal Aït Aoudia , Alex Keller
HEAT: Hardware-Efficient Automatic Tensor Decomposition for Transformer Compression
Jiaqi Gu, Ben Keller, Jean Kossaifi, Anima Anandkumar, Brucek Khailany, David Z. Pan
Spotlight Paper
An Adversarial Active Sampling-based Data Augmentation Framework for Manufacturable Chip Design
Mingjie Liu, Haoyu Yang, Zongyi Li, Kumara Sastry, Saumyadip Mukhopadhyay, Selim Dogru, Anima Anandkumar, David Z. Pan, Brucek Khailany, Haoxing (Mark) Ren
LNS-Madam: Low-Precision Training in Logarithmic Number System Using Multiplicative Weight Update
Jiawei Zhao, Steve Dai, Rangharajan Venkatesan, Brian Zimmer, Mustafa Ali, Ming-Yu Liu, Brucek Khailany, William Dally, Anima Anandkumar
Motion Policy Networks
Adam Fishman, Adithya Murali, Clemens Eppner, Bryan Peele, Byron Boots, Dieter Fox
"This is my unicorn, Fluffy": Personalizing frozen vision-language representations
Niv Cohen, Rinon Gal, Eli Meirom, Gal Chechik, Yuval Atzmon
Elucidating the Design Space of Diffusion-Based Generative Models
Tero Karras, Miika Aittala, Timo Aila, Samuli Laine
NeurIPS Outstanding Paper
LION: Latent Point Diffusion Models for 3D Shape Generation
Xiaohui Zeng, Arash Vahdat, Francis Williams, Zan Gojcic, Or Litany, Sanja Fidler, Karsten Kreis
Paraphrasing Is All You Need for Novel Object Captioning
Cheng-Fu Yang, Yao-Hung Hubert Tsai, Wan-Cyuan Fan, Ruslan Salakhutdinov, Louis-Philippe Morency, Frank Wang
SPoVT: Semantic-Prototype Variational Transformer for Dense Point Cloud Semantic Completion
Sheng-Yu Huang, Hao-Yu Hsu, Yu-Chiang Frank Wang
GENIE: Higher-Order Denoising Diffusion Solvers
Tim Dockhorn, Arash Vahdat, Karsten Kreis
Demystifying Map Space Exploration for NPUs
Sheng-Chun Kao, Angshuman Parashar, Po-An Tsai, Tushar Krishna
Towards Adaptive Digital Self-Interference Cancellation in Full-Duplex Wireless Transceivers: APSM vs. Neural Networks
M. Hossein Attar, Kaixin Chang, Ramez Askar, Slawomir Stanczak, Sebastian Cammerer, Guillermo Marcus, Alex Keller
Why are Graph Neural Networks Effective for EDA Problems?
Haoxing (Mark) Ren, Siddhartha Nath, Yanqing Zhang, Hao Chen, Mingjie Liu
TransSizer: A Novel Transformer-Based Fast Gate Sizer
Siddhartha Nath, Geraldo Pradipta, Corey Hu, Tian Yang, Brucek Khailany, Haoxing (Mark) Ren
TAG: Learning Circuit Spatial Embedding from Layouts
Keren Zhu, Hao Chen, Walker Turner, George F. Kokai, Po-Hsuan Wei, David Z. Pan, Haoxing (Mark) Ren
Heterogeneous-Agent Trajectory Forecasting Incorporating Class Uncertainty
Boris Ivanovic, Kuan-Hui Lee, Pavel Tokmakov, Blake Wulfe, Adrien Gaidon, Marco Pavone
Augmenting Legacy Networks for Flexible Inference.
Jason Clemons, Iuri Frosio, Maying Shen, Jose M. Alvarez, Steve Keckler
AdvDO: Realistic Adversarial Attacks for Trajectory Prediction
Yulong Cao, Chaowei Xiao, Anima Anandkumar, Danfei Xu, Marco Pavone
LANA: Latency Aware Network Acceleration
Pavlo Molchanov, Jimmy Hall, Hongxu Danny Yin, Jan Kautz, Nicolo Fusi, Arash Vahdat